IMAGE PROCESSING 2000+ MCQs

 1) At what points, a continuous image is digitized?

1. Sampling
2. Vertex
3. Contour
4. Random

Answer: a) Sampling points

Explanation: Sampling is a process of reducing continuous-time signals to discrete-time signals.

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2) ________ represents the transition between image function's continuous values and its digital equivalent.

1. Rasterization
2. Quantization
3. Sampling
4. None of the above

Answer: a) Quantization

Explanation: Quantization is a mechanism that involves the conversion of a continuous range of values into a finite range of discrete values.

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3) Which of the following correctly describes the slightest visible change in the level of intensity?

1. Contour
2. Saturation
3. Contrast
4. Intensity Resolution

Answer: d) Intensity Resolution

Explanation: Intensity resolution can be defined as the total number of bits required to quantize an image.

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4) What is the name of the tool that helps in zooming, shrinking, rotating, etc.?

1. Filters
2. Interpolation
3. Sampling
4. None of the above

Answer: b) Interpolation

Explanation: Interpolation is one such basic tool that is used to zoom, shrink, rotate, etc.

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5) The dynamic range of the imaging system is a quantitative relation where the upper limit can be determined by

1. Brightness
2. Contrast
3. Saturation
4. Noise

Answer: c) Saturation

Explanation: Saturation is taken as a numerator.

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6) The lower limit of the dynamic range ratio can be determined by

1. Brightness
2. Contrast
3. Saturation
4. Noise

Answer: d) Noise

Explanation: Noise is taken as a denominator.

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7) Which of the following is the most famous single sensor utilized for image acquisition?

1. Photodiode
2. CMOS
3. Microdensitometer
4. None of the above

Answer: a) Photodiode

Explanation: The photodiode is a p-n junction semiconductor device that transmutes the light into an electric current.

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8) What is the full form of CAT in image processing?

1. Computer-Aided Tomography
2. Computer-Aided Telegraphy
3. Computerized Axial Tomography
4. Computerized Axial Telegraphy

Answer: c) Computerized Axial Tomography

Explanation: Computerized Axial Tomography is based on image acquisition that uses sensor strips.

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9) What is meant by the section of the real plane that the image coordinates have spanned?

1. Coordinate Axis
2. Plane of Symmetry
3. Spatial Domain
4. None of the above

Answer: c) Spatial Domain

Explanation: Spatial Domain refers to the section of the real plane that has been spanned by the coordinates of an image, where x and y coordinates are called Spatial coordinates.

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10) Which of the following is the effect of using an inadequate amount of intensity levels in a digital image's smooth areas?

1. Contouring
2. Interpolation
3. Gaussian smooth
4. False Contouring

Answer: d) False Contouring

Explanation: False contouring is caused when the grey-level resolution of a digital image gets decreased.

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11) What is the name of the process in which the known data is utilized to evaluate the value at an unknown location?

1. Interpolation
2. Acquisition
3. Pixelation
4. None of the above

Answer: a) Interpolation

Explanation: Interpolation is a process that is employed in image resampling models for assessing unfamiliar locations.

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12) Which of the following is not a correct example of Image Multiplication?

1. Masking
2. Shading Correction
3. Pixelation
4. Region of Interest Operations

Answer: c) Pixelation

Explanation: Pixelation deals with the amplification of pixels.

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13) Name the procedure in which individual pixel values of the digital image get altered.

1. Neighborhood Operations
2. Image Registration
3. Geometric Spatial Transformation
4. Single Pixel Operation

Answer: d) Single Pixel Operation

Explanation: It is expressed as a transformation function T of the form s=T(z), where z is the intensity.

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14) Which of the following possess maximum frequency?

1. Gamma Rays
2. UV Rays
3. Microwaves
4. Radio waves

Answer: a) Gamma Rays

Explanation: Gamma rays are comprised of high-energy photons, which means gamma rays have the highest EM radiations. In the electromagnetic spectrum, "Gamma ray" is an arbitrary technology that encompasses a frequency above 300 EHz, 1 pm wavelength, and energy of 1.24 MeV.

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15) Which of the following color possess the longest wavelength in the visible spectrum?

1. Yellow
2. Red
3. Blue
4. Violet

Answer: b) Red

Explanation: In the visible spectrum, red has the longest wavelength. The visible colors are ranged from shortest to longest wavelength, i.e., Violet, Blue, Green, Yellow, Orange, and Red.

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16) What is the relationship between wavelength and frequency?

1. frequency = wavelength / c
2. c = wavelength / frequency
3. c = wavelength * frequency
4. wavelength = c * frequency

Answer: c) c = wavelength * frequency

Explanation: In general, the wavelength is calculated as wavelength = c / frequency, which means the higher the frequency, the lower the wavelength. In simple words, frequency is inversely proportional to the wavelength.

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17) _________ can be visualized as an electromagnetic wave.

1. cosine wave
2. sine wave
3. tangential wave
4. None of the above

Answer: b) sine wave

Explanation: Electromagnetic waves can be visualized as a sinusoidal wave.

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18) How to carry out an array function together with one or more images?

1. Pixel by Pixel
2. Column by Column
3. Array by Array
4. Row by Row

Answer: a) Pixel by Pixel

Explanation: The array function is carried out on a pixel-by-pixel basis.

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19) What is the name of the property that indicates the output of linear operation (i.e., the sum of two inputs) similar to that of operation first being performed on individual inputs and then summing up the respective outcomes?

1. Heterogeneity
2. Homogeneity
3. Additivity
4. None of the above

Answer: c) Additivity

Explanation: Additivity: f (a + b) = f (a) + f (b)

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20) What is the real-world application of image subtraction?

1. MRI scan
2. CT scan
3. Mask mode radiography
4. None of the above

Answer: c) Mask mode radiography

Explanation: Mask mode radiography is an important application of medical imaging in the area of image subtraction.

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21) What is meant by Region of Interest (ROI) operations?

1. Dilation
2. Masking
3. Shading correction
4. None of the above

Answer: b) Masking

Explanation: In image processing, masking is a procedure of defining a smaller image, which helps modify the larger image.

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22) If each element of set X is also an element of set Y, then X can be called ________ of set Y.

1. Union
2. Subset
3. Disjoint
4. Complement Set

Answer: b) Subset

Explanation: If all the elements of set X are contained in set Y, then X will be called a subset of Y.

Mathematically;

X ⊆ Y

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23) Blurring an image with the help of a smoothing filter may lead to noise reduction.

1. True
2. False

Answer: a) True

Explanation: Noise reduction is obtained by blurring the image using a smoothing filter. Blurring is used in pre-processing steps, such as removing small details from an image prior to object extraction and bridging small gaps in lines or curves.

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24) What is the output of a smoothing, linear spatial filter?

1. Median of pixels
2. Maximum of pixels
3. Minimum of pixels
4. Average of pixels

Answer: d) Average of pixels

Explanation: The output or response of smoothing, the linear spatial filter, is simply the average of the pixels contained in the neighborhood of the filter mask.

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25) A smoothing filter can also be called a median filter.

1. True
2. False

Answer: b) False

Explanation: A smoothing filter is used to calculate the average of the filter, which is the only reason it is called an average filter.

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26) Smoothing filter is used to remove __________ from an image.

1. Smooth transitions of brightness levels
2. Smooth transitions of grey levels
3. Sharp transitions of brightness levels
4. Sharp transitions of grey levels.

Answer: d) Sharp transitions of grey levels

Explanation: The smoothing filter helps in substituting each pixel value of an image by computing the average value of grey levels, which will further remove the sharp transitions in the grey levels amid the pixels. This is just to randomize noise that consists of sharp transitions in the grey level.

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27) Which of the following is the disadvantage of a smoothing filter?

1. Blur inner pixels
2. Blur edges
3. Sharp edges
4. Remove sharp transitions

Answer: b) Blur edges

Explanation: Edges are one of the most desirable features that can be categorized by sharp transitions in the grey levels. Thus, average filters blur the edges, causing unwanted side effects on the image.

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28) A smoothing spatial filter cannot smooth the false contour.

1. True
2. False

Answer: b) False

Explanation: The smoothing spatial filter removes the false contour that is caused due to an insufficient number of grey levels.

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29) Which of the following is the correct application of image blurring?

1. Gross representation
2. Object motion
3. Object detection
4. Image segmentation

Answer: a) Gross representation

Explanation: The main purpose of gross representation is to blur the image, which is one of the most significant applications of spatial averaging. This is just to intensify the small objects combined with the background and large objects so that they can be easily identified.

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30) Median filters belong to which category of filter?

1. Frequency Domain Filter
2. Order Static Filter
3. Linear Spatial Filter
4. Sharpening Filter

Answer: b) Order Static Filter

Explanation: The median filter belongs to the order static filter, which substitutes the pixel value by the median of grey level that exists in the neighborhood of the pixel.

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31) Which of the following is the correct representation of log transformation?

1. s=clog₁₀(1+r)
2. s=clog₁₀(1/r)
3. s=clog₁₀(1-r)
4. s=clog₁₀(1*r)

Answer: b) s=clog₁₀(1+r)

Explanation: In general, log transformation can be formulized as; s=clog₁₀(1+r), where c is constant and r ≥ 0.

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32) Which of the following the general representation of power transformation?

1. c = sr^y
2. s = rc^y
3. s = cr^y
4. s = rc

Answer: c) s = cr^y

Explanation: The power-law transformation can be mathematically derived as; s = cr^y, where c and g represent the positive constants. However, we can write the same equation in another way, such as s=c. (r + ε) ^γ, which represents an offset.

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33) Which of the following requires to specify the information at the time of input?

1. Power transformation
2. Log transformation
3. Linear transformation
4. Piece-wise transformation

Answer: d) Piece-wise transformation

Explanation: Piece-wise transformation plays a vital role while formulating some other transformations. Its only disadvantage is that it requires a considerable number of inputs.

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34) A second order derivative operator can be defined as __________.

1. Laplacian
2. Gaussian
3. Histogram
4. None of the above

Answer: a) Laplacian

Explanation: Laplacian is the second-order derivative operator.

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35) Which of the following is used to resolve the dark features in the image?

1. Gaussian Transform
2. Laplacian Transform
3. Power-law Transformation
4. Histogram Specification

Answer: c) Power-law Transform

Explanation: The dark features can be easily resolved by histogram specification. However, to get the desired result, power-law transformation is highly suggested over histogram specification.

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36) What is the smallest possible value of the gradient image?

1. 1
2. 0
3. e
4. -e

Answer: b) 0

Explanation: The smallest possible value of the gradient image is 0.

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37) Which of the following filter possess lower frequency?

1. High pass filter
2. Bandpass filter
3. Low pass filter
4. None of the above

Answer: c) Low pass filter

Explanation: A low pass filter passes a low frequency.

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38) What is the name of the process that moves a filter mask over the image, followed by calculating the sum of products?

1. Correlation
2. Convolution
3. Linear spatial filtering
4. Non-linear spatial filtering

Answer: a) Correlation

Explanation: Correlation can be defined as the process of moving a filter, which is often denoted as a kernel over the image to compute the sum of products at each distinct location.

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39) Which of the following fact is true for an image?

1. An image is the subtraction of the illumination component from the reflectance component.
2. An image is the multiplication of the illumination and reflectance component.
3. An image is the addition of illumination and reflectance component
4. An image is the subtraction of the reflectance component from the illumination component

Answer: b) An image is the multiplication of illumination and reflectance component

Explanation: An image can be expressed as the multiplication of illumination and reflectance components.

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40) Which of the following operations is used in homographic filtering for converting the input image to discrete Fourier transformed function?

1. Exponential Function
2. Logarithmic Function
3. Negative Function
4. None of the above

Answer: b) Logarithmic Function

Explanation: An image can be expressed as the multiplication of illumination and reflectance component i.e. f(x, y) = i(x, y) * r(x, y). The equation can't be used directly to operate separately on the frequency component of illumination and reflectance because the Fourier transform of the product of two function is not separable. So, the logarithmic operation is used. I{z(x,y)}=I{ln(f(x,y)) }=I{ln(i(x,y)) }+I{ln(r(x,y))}.

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41) What is the name of the class that accepts an image's separation of luminesce and reflectance component?

1. Homomorphic system
2. Base class system
3. Base separation system
4. All of the above

Answer: a) Homomorphic system

Explanation: A homomorphic system is the only class of a system that helps achieve the separation of luminesce and reflectance components of an image.

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42) Which of the following image component abruptly diverges at a certain junction of distinct objects?

1. Reflectance component
2. Illumination component
3. Both (a) and (b)
4. None of the above

Answer: b) Reflectance component

Explanation: Whenever an object reflects some light onto the scene, then the total amount of light that has been mirrored is termed as the reflectance component.

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43) Given an intensity level [0, L-1] with "r" and "s" positive values, how will the negative of an image obtain?

1. s = L - 1 - r
2. s = L - 1 + r
3. s = L + 1 - r
4. s = L + 1 + r

Answer: a) s = L - 1 - r

Explanation: The negative of an image will be obtain by s = L - 1 - r.

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44) In general, the log transformation can be represented by _________

1. s = c.log (1 - r)
2. s = c - log (1 - r)
3. s = c.log (1 + r)
4. s = c + log (1 + r)

Answer: c) s = c.log (1 + r)

Explanation: The general form of log transformation is s = c.log (1 + r).

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45) Which of the following is the correct definition of Gamma correction?

1. Light brightness variation
2. A Power-law response phenomenon
3. Inverted intensity curve
4. None of the above

Answer: b) A Power-law response phenomenon

Explanation: In order to compensate for the effects of non-linear luminance, the gamma correction function maps the levels of luminance, where γ refers to a constant, i.e., gamma, and "^" is the power operator.

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46) What is the name of the process that highlights an image's intensity?

1. Intensity Highlighting
2. Intensity Matching
3. Intensity Slicing
4. None of the above

Answer: c) Intensity Slicing

Explanation: Intensity Slicing is a process of highlighting the intensity of an image.

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47) What is the name of the process, which reverses the image's intensity?

1. Piecewise Linear Transformations
2. Image Negatives
3. Log Transformations
4. None of the above

Answer: b) Image Negatives

Explanation: Image negatives utilize the reverse of image intensity.

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48) Which of the following grey level intensities help in increasing the grey levels dynamic range in the image?

1. Contrast Stretching
2. Negative Transformations
3. Power-law Transformations
4. None of the above

Answer: a) Contrast Stretching

Explanation: Contrast stretching is a process of augmenting an image's quality, which improves its contrast by stretching.

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49) What is the main idea behind grey-level slicing?

1. For brightening the relevant grey-valued pixels and preserving the background
2. To give all grey levels of a specific range high value and a low value to all other grey levels.
3. All of the above
4. None of the above

Answer: c) All of the above

Explanation: In general, grey-level slicing includes the following two types of approaches:

• The first one includes assigning all grey levels of a specific range high value and a low value to all other grey levels.
• However, the second approach not only brightens the relevant grey-level pixel value but also preserves the background.

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50) Which of the following technique is used to obtain a certain range of bits required to quantize each pixel?

1. Contouring
2. Bit-plane slicing
3. Grey-level slicing
4. Contrast stretching

Answer: b) Bit-plane slicing

Explanation: Bit-plane slicing is one such method that represents an image with more than one bit of a byte that has been utilized for each pixel.

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51) In which of the following areas can we use the low pass filters?

1. Machine perception, along with some application of character recognition
2. Printing and publishing industry
3. Satellite processing and aerial images
4. All of the above

Answer: d) All of the above

Explanation: The Lowpass filter concept is utilized in the field of character recognition, publishing, and printing industry and in the case of remotely sensed images as well by simply blurring the irrelevant data to reveal more prominent features out of the full image.

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52) Which of the following act as a receptor in the retina of a human eye?

1. Cones
2. Rods
3. Both (a) and (b)
4. Neither (a) nor (b)

Answer: c) Both (a) and (b)

Explanation: Rods are long slender receptors, while cones are shorter and thicker receptors.

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53) Subjective brightness is related to __________

1. Brightness
2. Intensity
3. Image Perception
4. Image Formation

Answer: b) Intensity

Explanation: Subjective brightness is related to intensity, which is perceived by the human eye.

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54) What is the name of the innermost membrane present in the human eye?

1. Sclera
2. Choroid
3. Retina
4. Blindspot

Answer: c) Retina

Explanation: The retina is the innermost membrane of the human eye.

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55) What is defined by the total number of pixels within the region?

1. Area
2. Brightness
3. Intensity
4. Perimeter

Answer: a) Area

Explanation: The total number of pixels within the region defines the area of that region. However, the perimeter refers to the boundary of the region, given the number of pixels.

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56) For which of the following regions, minimal compactness is required?

1. Disk
2. Square
3. Irregular
4. Rectangle

Answer: a) Disk

Explanation: Since the compactness of a region is defined by 2 * (Parameter)/ Area, so the disk-shaped region encompasses minimal compactness.

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57) _________ is the principal factor, which helps in determining an image's spatial resolution.

1. Dynamic range
2. Quantization
3. Sampling
4. Contrast

Answer: c) Sampling

Explanation: The spatial resolution of an image can be principally determined by the process called sampling.

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58) What is meant by a band-limited function?

1. A function of limited duration whose highest frequency is finite
2. A function of limited duration whose highest frequency is infinite
3. All of the abov

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59) What is the sum of all components of a normalized histogram?

1. 1
2. -1
3. 0
4. None of the above

Answer: a) 1

Explanation: A normalized histogram can be mathematically defined by;

p(r_k) = n_k / n

where n represents the total number of pixels contained in an image, r_k represents the kth grey-level, and n_k is the total number of pixels with grey-level r_k.

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60) The technique of Enhancement that has a specified Histogram processed image, as a result, is called?

1. Histogram Linearization
2. Histogram Equalization
3. Histogram Matching
4. None of the above

5. Answer: c) Histogram Matching

   Explanation: In general, histogram specification uses a specified Histogram, i.e., the shape of the histogram can be specified by self to generate a processed image, which is also called Histogram Matching.

1. A continuous image is digitised at _______ points.
a) random
b) vertex
c) contour
d) sampling

Answer: d
Explanation: The sampling points are ordered in the plane and their relation is called a Grid.

2. The transition between continuous values of the image function and its digital equivalent is called ______________
a) Quantisation
b) Sampling
c) Rasterisation
d) None of the Mentioned

Answer: a
Explanation: The transition between continuous values of the image function and its digital equivalent is called Quantisation.

3. Images quantised with insufficient brightness levels will lead to the occurrence of ____________
a) Pixillation
b) Blurring
c) False Contours
d) None of the Mentioned

Answer: c
Explanation: This effect arises when the number brightness levels is lower that which the human eye can distinguish.

4. The smallest discernible change in intensity level is called ____________
a) Intensity Resolution
b) Contour
c) Saturation
d) Contrast

Answer: a
Explanation: Number of bits used to quantise intensity of an image is called intensity resolution.

5. What is the tool used in tasks such as zooming, shrinking, rotating, etc.?
a) Sampling
b) Interpolation
c) Filters
d) None of the Mentioned

Answer: b
Explanation: Interpolation is the basic tool used for zooming, shrinking, rotating, etc.

6. The type of Interpolation where for each new location the intensity of the immediate pixel is assigned is ___________
a) bicubic interpolation
b) cubic interpolation
c) bilinear interpolation
d) nearest neighbour interpolation

Answer: d
Explanation: Its called as Nearest Neighbour Interpolation since for each new location the intensity of the next neighbouring pixel is assigned.

7. The type of Interpolation where the intensity of the FOUR neighbouring pixels is used to obtain intensity a new location is called ___________
a) cubic interpolation
b) nearest neighbour interpolation
c) bilinear interpolation
d) bicubic interpolation

Answer: b
Explanation: Bilinear interpolation is where the FOUR neighbouring pixels is used to estimate intensity for a new location.

8. Dynamic range of imaging system is a ratio where the upper limit is determined by
a) Saturation
b) Noise
c) Brightness
d) Contrast

Answer: a
Explanation: Saturation is taken as the Numerator.

9. For Dynamic range ratio the lower limit is determined by
a) Saturation
b) Brightness
c) Noise
d) Contrast

Answer: c
Explanation: Noise is taken as the Denominator.

10. Quantitatively, spatial resolution cannot be represented in which of the following ways
a) line pairs
b) pixels
c) dots
d) none of the Mentioned

Answer: d
Explanation: All the options can be used to represent spatial resolution

1. The most familiar single sensor used for Image Acquisition is

a) Microdensitometer

b) Photodiode

c) CMOS

d) None of the Mentioned

  

Answer: b

Explanation: Photodiode is the most commonly used single sensor made up of silicon materials.

2. A geometry consisting of in-line arrangement of sensors for image acquisition

a) A photodiode

b) Sensor strips

c) Sensor arrays

d) CMOS

  

Answer: b

Explanation: Sensor strips are very common next to single sensor and use in-line arrangement.

3. CAT in imaging stands for

a) Computer Aided Telegraphy

b) Computer Aided Tomography

c) Computerised Axial Telegraphy

d) Computerised Axial Tomography

  

Answer: d

Explanation: Industrial Computerised Axial Tomography is based on image acquisition using sensor strips.

4. The section of the real plane spanned by the coordinates of an image is called the _____________

a) Spacial Domain

b) Coordinate Axes

c) Plane of Symmetry

d) None of the Mentioned

  

Answer: a

Explanation: The section of the real plane spanned by the coordinates of an image is called the Spacial Domain, with the x and y coordinates referred to as Spacial coordinates.

5. The difference is intensity between the highest and the lowest intensity levels in an image is ___________

a) Noise

b) Saturation

c) Contrast

d) Brightness

  

Answer: c

Explanation: Contrast is the measure of the difference is intensity between the highest and the lowest intensity levels in an image.

6. _____________ is the effect caused by the use of an insufficient number of intensity levels in smooth areas of a digital image.

a) Gaussian smooth

b) Contouring

c) False Contouring

d) Interpolation

  

Answer: c

Explanation: It is called so because the ridges resemble the contours of a map.

7. The process of using known data to estimate values at unknown locations is called

a) Acquisition

b) Interpolation

c) Pixelation

d) None of the Mentioned

  

Answer: b

Explanation: Interpolation is the process used to estimate unknown locations. It is applied in all image resampling methods.

8. Which of the following is NOT an application of Image Multiplication?

a) Shading Correction

b) Masking

c) Pixelation

d) Region of Interest operations

  

Answer: c

Explanation: Because Pixelation deals with enlargement of pixels.

9. The procedure done on a digital image to alter the values of its individual pixels is

a) Neighbourhood Operations

b) Image Registration

c) Geometric Spacial Transformation

d) Single Pixel Operation

  

Answer: d

Explanation: It is expressed as a transformation function T, of the form s=T(z) , where z is the intensity.

10. In Geometric Spacial Transformation, points whose locations are known precisely in input and reference images.

a) Tie points

b) Réseau points

c) Known points

d) Key-points

  

Answer: a

Explanation: Tie points, also called Control points are points whose locations are known precisely in input and reference images.

1. Of the following, _________ has the maximum frequency.

a) UV Rays

b) Gamma Rays

c) Microwaves

d) Radio Waves

   

Answer: b

Explanation: Gamma Rays come first in the electromagnetic spectrum sorted in the decreasing order of frequency.

2. In the Visible spectrum the ______ colour has the maximum wavelength.

a) Violet

b) Blue

c) Red

d) Yellow

   

Answer: c

Explanation: Red is towards the right in the electromagnetic spectrum sorted in the increasing order of wavelength.

3. Wavelength and frequency are related as : (c = speed of light)

a) c = wavelength / frequency

b) frequency = wavelength / c

c) wavelength = c * frequency

d) c = wavelength * frequency

   

Answer: d

Explanation: It is usually written as wavelength = c / frequency.

4. Electromagnetic waves can be visualised as a

a) sine wave

b) cosine wave

c) tangential wave

d) None of the mentioned

   

Answer: a

Explanation: Electromagnetic waves are visualised as sinusoidal wave.

5. How is radiance measured?

a) lumens

b) watts

c) armstrong

d) hertz

   

Answer: b

Explanation: Radiance is the total amount of energy that flows from the light source and is measured in Watts.

6. Which of the following is used for chest and dental scans?

a) Hard X-Rays

b) Soft X-Rays

c) Radio waves

d) Infrared Rays

   

Answer: b

Explanation: Soft X-Rays (low energy) are used for dental and chest scans.

7. Which of the following is impractical to measure?

a) Frequency

b) Radiance

c) Luminance

d) Brightness

   

Answer: d

Explanation: Brightness is subjective descriptor of light perception that is impossible to measure.

8. Massless particle containing a certain amount of energy is called

a) Photon

b) Shell

c) Electron

d) None of the mentioned

   

Answer: a

Explanation: Each bundle of massless energy is called a Photon.

9. What do you mean by achromatic light?

a) Chromatic light

b) Monochromatic light

c) Infrared light

d) Invisible light

   

Answer: b

Explanation: Achromatic light is also called monochromatic light.(Light void of color)

10. Which of the following embodies the achromatic notion of intensity?

a) Luminance

b) Brightness

c) Frequency

d) Radiance

   

Answer: b

Explanation: Brightness embodies the achromatic notion of intensity and is a key factor in describing color sensation.

1. How is array operation carried out involving one or more images?

a) array by array

b) pixel by pixel

c) column by column

d) row by row

   

Answer: b

Explanation: Any array operation is carried out on a pixel by pixel basis.

2. The property indicating that the output of a linear operation due to the sum of two inputs is same as performing the operation on the inputs individually and then summing the results is called ___________

a) additivity

b) heterogeneity

c) homogeneity

d) None of the Mentioned

   

Answer: a

Explanation: This property is called additivity .

3. The property indicating that the output of a linear operation to a constant times as input is the same as the output of operation due to original input multiplied by that constant is called _________

a) additivity

b) heterogeneity

c) homogeneity

d) None of the Mentioned

   

Answer: c

Explanation: This property is called homogeneity .

4. Enhancement of differences between images is based on the principle of ____________

a) Additivity

b) Homogeneity

c) Subtraction

d) None of the Mentioned

   

Answer: c

Explanation: A frequent application of image subtraction is in the enhancement of differences between images .

5. A commercial use of Image Subtraction is ___________

a) Mask mode radiography

b) MRI scan

c) CT scan

d) None of the Mentioned

   

Answer: a

Explanation: Mask mode radiography is an important medical imaging area based on Image Subtraction.

6. Region of Interest (ROI) operations is commonly called as ___________

a) Shading correction

b) Masking

c) Dilation

d) None of the Mentioned

   

Answer: b

Explanation: A common use of image multiplication is Masking, also called ROI operation.

7. If every element of a set A is also an element of a set B, then A is said to be a _________ of set B.

a) Disjoint set

b) Union

c) Subset

d) Complement set

   

Answer: c

Explanation: A is called the subset of B.

8. Consider two regions A and B composed of foreground pixels. The ________ of these two sets is the set of elements belonging to set A or set B or both.

a) OR

b) AND

c) NOT

d) XOR

   

Answer: a

Explanation: This is called an OR operation.

9. Imaging systems having physical artefacts embedded in the imaging sensors produce a set of points called __________

a) Tie Points

b) Control Points

c) Reseau Marks

d) None of the Mentioned

   

Answer: c

Explanation: These points are called “known” points or “Reseau marks”.

10. Image processing approaches operating directly on pixels of input image work directly in ____________

a) Transform domain

b) Spatial domain

c) Inverse transformation

d) None of the Mentioned

   

Answer: b

Explanation: Operations directly on pixels of input image work directly in Spatial Domain.

1. Noise reduction is obtained by blurring the image using smoothing filter.

a) True

b) False

   

Answer: a

Explanation: Noise reduction is obtained by blurring the image using smoothing filter. Blurring is used in pre-processing steps, such as removal of small details from an image prior to object extraction and, bridging of small gaps in lines or curves.

2. What is the output of a smoothing, linear spatial filter?

a) Median of pixels

b) Maximum of pixels

c) Minimum of pixels

d) Average of pixels

   

Answer: d

Explanation: The output or response of a smoothing, linear spatial filter is simply the average of the pixels contained in the neighbourhood of the filter mask.

3. Smoothing linear filter is also known as median filter.

a) True

b) False

   

Answer: b

Explanation: Since the smoothing spatial filter performs the average of the pixels, it is also called as averaging filter.

4. Which of the following in an image can be removed by using smoothing filter?

a) Smooth transitions of gray levels

b) Smooth transitions of brightness levels

c) Sharp transitions of gray levels

d) Sharp transitions of brightness levels

   

Answer: c

Explanation: Smoothing filter replaces the value of every pixel in an image by the average value of the gray levels. So, this helps in removing the sharp transitions in the gray levels between the pixels. This is done because, random noise typically consists of sharp transitions in gray levels.

5. Which of the following is the disadvantage of using smoothing filter?

a) Blur edges

b) Blur inner pixels

c) Remove sharp transitions

d) Sharp edges

   

Answer: a

Explanation: Edges, which almost always are desirable features of an image, also are characterized by sharp transitions in gray level. So, averaging filters have an undesirable side effect that they blur these edges.

6. Smoothing spatial filters doesn’t smooth the false contours.

a) True

b) False

   

Answer: b

Explanation: One of the application of smoothing spatial filters is that, they help in smoothing the false contours that result from using an insufficient number of gray levels.

7. The mask shown in the figure below belongs to which type of filter?

digital-image-processing-questions-answers-smoothing-spatial-filters-q7

a) Sharpening spatial filter

b) Median filter

c) Sharpening frequency filter

d) Smoothing spatial filter

   

Answer: d

Explanation: This is a smoothing spatial filter. This mask yields a so called weighted average, which means that different pixels are multiplied with different coefficient values. This helps in giving much importance to the some pixels at the expense of others.

8. The mask shown in the figure below belongs to which type of filter?

digital-image-processing-questions-answers-smoothing-spatial-filters-q8

a) Sharpening spatial filter

b) Median filter

c) Smoothing spatial filter

d) Sharpening frequency filter

   

Answer: c

Explanation: The mask shown in the figure represents a 3×3 smoothing filter. Use of this filter yields the standard average of the pixels under the mask.

9. Box filter is a type of smoothing filter.

a) True

b) False

   

Answer: a

Explanation: A spatial averaging filter or spatial smoothening filter in which all the coefficients are equal is also called as box filter.

10. If the size of the averaging filter used to smooth the original image to first image is 9, then what would be the size of the averaging filter used in smoothing the same original picture to second in second image?

digital-image-processing-questions-answers-smoothing-spatial-filters-q10

a) 3

b) 5

c) 9

d) 15

   

Answer: d

Explanation: We know that, as the size of the filter used in smoothening the original image that is averaging filter increases then the blurring of the image. Since the second image is more blurred than the first image, the window size should be more than 9.

11. Which of the following comes under the application of image blurring?

a) Object detection

b) Gross representation

c) Object motion

d) Image segmentation

   

Answer: b

Explanation: An important application of spatial averaging is to blur an image for the purpose of getting a gross representation of interested objects, such that the intensity of the small objects blends with the background and large objects become easy to detect.c

12. Which of the following filters response is based on ranking of pixels?

a) Nonlinear smoothing filters

b) Linear smoothing filters

c) Sharpening filters

d) Geometric mean filter

   

Answer: a

Explanation: Order static filters are nonlinear smoothing spatial filters whose response is based on the ordering or ranking the pixels contained in the image area encompassed by the filter, and then replacing the value of the central pixel with the value determined by the ranking result.

13. Median filter belongs to which category of filters?

a) Linear spatial filter

b) Frequency domain filter

c) Order static filter

d) Sharpening filter

   

Answer: c

Explanation: The median filter belongs to order static filters, which, as the name implies, replaces the value of the pixel by the median of the gray levels that are present in the neighbourhood of the pixels.

14. Median filters are effective in the presence of impulse noise.

a) True

b) False

   

Answer: a

Explanation: Median filters are used to remove impulse noises, also called as salt-and-pepper noise because of its appearance as white and black dots in the image.

15. What is the maximum area of the cluster that can be eliminated by using an n×n median filter?

a) n2

b) n2/2

c) 2*n2

d) n

   

Answer: b

Explanation: Isolated clusters of pixels that are light or dark with respect to their neighbours, and whose area is less than n2/2, i.e., half the area of the filter, can be eliminated by using an n×n median filter.

1. Which of the following expression is used to denote spatial domain process?

a) g(x,y)=T[f(x,y)]

b) f(x+y)=T[g(x+y)]

c) g(xy)=T[f(xy)]

d) g(x-y)=T[f(x-y)]

   

Answer: a

Explanation: Spatial domain processes will be denoted by the expression g(x,y)=T[f(x,y)], where f(x,y) is the input image, g(x,y) is the processed image, and T is an operator on f, defined over some neighborhood of (x, y). In addition, T can operate on a set of input images, such as performing the pixel-by-pixel sum of K images for noise reduction.

2. Which of the following shows three basic types of functions used frequently for image enhancement?

a) Linear, logarithmic and inverse law

b) Power law, logarithmic and inverse law

c) Linear, logarithmic and power law

d) Linear, exponential and inverse law

   

Answer: b

Explanation: In introduction to gray-level transformations, which shows three basic types of functions used frequently for image enhancement: linear (negative and identity transformations), logarithmic (log and inverse-log transformations), and power-law (nth power and nth root transformations).The identity function is the trivial case in which output intensities are identical to input intensities. It is included in the graph only for completeness.

3. Which expression is obtained by performing the negative transformation on the negative of an image with gray levels in the range[0,L-1] ?

a) s=L+1-r

b) s=L+1+r

c) s=L-1-r

d) s=L-1+r

   

Answer: c

Explanation: The negative of an image with gray levels in the range[0,L-1] is obtained by using the negative transformation, which is given by the expression: s=L-1-r.

4. What is the general form of representation of log transformation?

a) s=clog10(1/r)

b) s=clog10(1+r)

c) s=clog10(1*r)

d) s=clog10(1-r)

   

Answer: b

Explanation: The general form of the log transformation: s=clog10(1+r), where c is a constant, and it is assumed that r ≥ 0.

5. What is the general form of representation of power transformation?

a) s=crγ

b) c=srγ

c) s=rc

d) s=rcγ

   

Answer: a

Explanation: Power-law transformations have the basic form: s=crγ where c and g are positive constants. Sometimes s=crγ is written as s=c.(r+ε)γ to account for an offset (that is, a measurable output when the input is zero).

6. What is the name of process used to correct the power-law response phenomena?

a) Beta correction

b) Alpha correction

c) Gamma correction

d) Pie correction

   

Answer: c

Explanation: A variety of devices used for image capture, printing, and display respond according to a power law. By convention, the exponent in the power-law equation is referred to as gamma .The process used to correct these power-law response phenomena is called gamma correction.

7. Which of the following transformation function requires much information to be specified at the time of input?

a) Log transformation

b) Power transformation

c) Piece-wise transformation

d) Linear transformation

   

Answer: c

Explanation: The practical implementation of some important transformations can be formulated only as piecewise functions. The principal disadvantage of piecewise functions is that their specification requires considerably more user input.

8. In contrast stretching, if r1=s1 and r2=s2 then which of the following is true?

a) The transformation is not a linear function that produces no changes in gray levels

b) The transformation is a linear function that produces no changes in gray levels

c) The transformation is a linear function that produces changes in gray levels

d) The transformation is not a linear function that produces changes in gray levels

   

Answer: b

Explanation: The locations of points (r1,s1) and (r2,s2) control the shape of the transformation function. If r1=s1 and r2=s2 then the transformation is a linear function that produces no changes in gray levels.

9. In contrast stretching, if r1=r2, s1=0 and s2=L-1 then which of the following is true?

a) The transformation becomes a thresholding function that creates an octal image

b) The transformation becomes a override function that creates an octal image

c) The transformation becomes a thresholding function that creates a binary image

d) The transformation becomes a thresholding function that do not create an octal image

   

Answer: c

Explanation: If r1=r2, s1=0 and s2=L-1,the transformation becomes a thresholding function that creates a binary image.

10. In contrast stretching, if r1≤r2 and s1≤s2 then which of the following is true?

a) The transformation function is double valued and exponentially increasing

b) The transformation function is double valued and monotonically increasing

c) The transformation function is single valued and exponentially increasing

d) The transformation function is single valued and monotonically increasing

   

Answer: d

Explanation: The locations of points (r1,s1) and (r2,s2) control the shape of the transformation function. If r1≤r2 and s1≤s2 then the function is single valued and monotonically increasing.

11. In which type of slicing, highlighting a specific range of gray levels in an image often is desired?

a) Gray-level slicing

b) Bit-plane slicing

c) Contrast stretching

d) Byte-level slicing

   

Answer: a

Explanation: Highlighting a specific range of gray levels in an image often is desired in gray-level slicing. Applications include enhancing features such as masses of water in satellite imagery and enhancing flaws in X-ray images.

12. Which of the following depicts the main functionality of the Bit-plane slicing?

a) Highlighting a specific range of gray levels in an image

b) Highlighting the contribution made to total image appearance by specific bits

c) Highlighting the contribution made to total image appearance by specific byte

d) Highlighting the contribution made to total image appearance by specific pixels

   

Answer: b

Explanation: Instead of highlighting gray-level ranges, highlighting the contribution made to total image appearance by specific bits might be desired. Suppose , each pixel in an image is represented by 8 bits. Imagine that the image is composed of eight 1-bit planes, ranging from bit-plane 0 for the least significant bit to bit-plane 7 for the most significant bit. In terms of 8-bit bytes, plane 0 contains all the lowest order bits in the bytes comprising the pixels in the image and plane 7 contains all the high-order bits.

1. Which of the following is the primary objective of sharpening of an image?

a) Blurring the image

b) Highlight fine details in the image

c) Increase the brightness of the image

d) Decrease the brightness of the image

   

Answer: b

Explanation: The sharpening of image helps in highlighting the fine details that are present in the image or to enhance the details that are blurred due to some reason like adding noise.

2. Image sharpening process is used in electronic printing.

a) True

b) False

   

Answer: a

Explanation: The applications of image sharpening is present in various fields like electronic printing, autonomous guidance in military systems, medical imaging and industrial inspection.

3. In spatial domain, which of the following operation is done on the pixels in sharpening the image?

a) Integration

b) Average

c) Median

d) Differentiation

   

Answer: d

Explanation: We know that, in blurring the image, we perform the average of pixels which can be considered as integration. As sharpening is the opposite process of blurring, logically we can tell that we perform differentiation on the pixels to sharpen the image.

4. Image differentiation enhances the edges, discontinuities and deemphasizes the pixels with slow varying gray levels.

a) True

b) False

   

Answer: a

Explanation: Fundamentally, the strength of the response of the derivative operative is proportional to the degree of discontinuity in the image. So, we can state that image differentiation enhances the edges, discontinuities and deemphasizes the pixels with slow varying gray levels.

5. In which of the following cases, we wouldn’t worry about the behaviour of sharpening filter?

a) Flat segments

b) Step discontinuities

c) Ramp discontinuities

d) Slow varying gray values

   

Answer: d

Explanation: We are interested in the behaviour of derivatives used in sharpening in the constant gray level areas i.e., flat segments, and at the onset and end of discontinuities, i.e., step and ramp discontinuities.

6. Which of the following is the valid response when we apply a first derivative?

a) Non-zero at flat segments

b) Zero at the onset of gray level step

c) Zero in flat segments

d) Zero along ramps

   

Answer: c

Explanation: The derivations of digital functions are defined in terms of differences. The definition we use for first derivative should be zero in flat segments, nonzero at the onset of a gray level step or ramp and nonzero along the ramps.

7. Which of the following is not a valid response when we apply a second derivative?

a) Zero response at onset of gray level step

b) Nonzero response at onset of gray level step

c) Zero response at flat segments

d) Nonzero response along the ramps

   

Answer: b

Explanation: The derivations of digital functions are defined in terms of differences. The definition we use for second derivative should be zero in flat segments, zero at the onset of a gray level step or ramp and nonzero along the ramps.

8. If f(x,y) is an image function of two variables, then the first order derivative of a one dimensional function, f(x) is:

a) f(x+1)-f(x)

b) f(x)-f(x+1)

c) f(x-1)-f(x+1)

d) f(x)+f(x-1)

   

Answer: a

Explanation: The first order derivative of a single dimensional function f(x) is the difference between f(x) and f(x+1).

That is, ∂f/∂x=f(x+1)-f(x).

9. Isolated point is also called as noise point.

a) True

b) False

   

Answer: a

Explanation: The point which has very high or very low gray level value compared to its neighbours, then that point is called as isolated point or noise point. The noise point of is of one pixel size.

10. What is the thickness of the edges produced by first order derivatives when compared to that of second order derivatives?

a) Finer

b) Equal

c) Thicker

d) Independent

   

Answer: c

Explanation: We know that, the first order derivative is nonzero along the entire ramp while the second order is zero along the ramp. So, we can conclude that the first order derivatives produce thicker edges and the second order derivatives produce much finer edges.

11. First order derivative can enhance the fine detail in the image compared to that of second order derivative.

a) True

b) False

   

Answer: b

Explanation: The response at and around the noise point is much stronger for the second order derivative than for the first order derivative. So, we can state that the second order derivative is better to enhance the fine details in the image including noise when compared to that of first order derivative.

12. Which of the following derivatives produce a double response at step changes in gray level?

a) First order derivative

b) Third order derivative

c) Second order derivative

d) First and second order derivatives

   

Answer: c

Explanation: Second order derivatives produce a double line response for the step changes in the gray level. We also note of second-order derivatives that, for similar changes in gray-level values in an image, their response is stronger to a line than to a step, and to a point than to a line.

1. The objective of sharpening spatial filters is/are to ___________

a) Highlight fine detail in an image

b) Enhance detail that has been blurred because of some error

c) Enhance detail that has been blurred because of some natural effect of some method of image acquisition

d) All of the mentioned

   

Answer: d

Explanation: Highlighting the fine detail in an image or Enhancing detail that has been blurred because of some error or some natural effect of some method of image acquisition, is the principal objective of sharpening spatial filters.

2. Sharpening is analogous to which of the following operations?

a) To spatial integration

b) To spatial differentiation

c) All of the mentioned

d) None of the mentioned

   

Answer: b

Explanation: Smoothing is analogous to integration and so, sharpening to spatial differentiation.

3. Which of the following fact(s) is/are true about sharpening spatial filters using digital differentiation?

a) Sharpening spatial filter response is proportional to the discontinuity of the image at the point where the derivative operation is applied

b) Sharpening spatial filters enhances edges and discontinuities like noise

c) Sharpening spatial filters deemphasizes areas that have slowly varying gray-level values

d) All of the mentioned

   

Answer: d

Explanation: Derivative operator’s response is proportional to the discontinuity of the image at the point where the derivative operation is applied.

Image differentiation enhances edges and discontinuities like noise and deemphasizes areas that have slowly varying gray-level values.

Since a sharpening spatial filters are analogous to differentiation, so, all the above mentioned facts are true for sharpening spatial filters.

4. Which of the facts(s) is/are true for the first order derivative of a digital function?

a) Must be nonzero in the areas of constant grey values

b) Must be zero at the onset of a gray-level step or ramp discontinuities

c) Must be nonzero along the gray-level ramps

d) None of the mentioned

   

Answer: c

Explanation: The first order derivative of a digital function is defined as:

Must be zero in the areas of constant grey values.

Must be nonzero at the onset of a gray-level step or ramp discontinuities.

Must be nonzero along the gray-level ramps.

5. Which of the facts(s) is/are true for the second order derivative of a digital function?

a) Must be zero in the flat areas

b) Must be nonzero at the onset and end of a gray-level step or ramp discontinuities

c) Must be zero along the ramps of constant slope

d) All of the mentioned

   

Answer: c

Explanation: The second order derivative of a digital function is defined as:

Must be zero in the flat areas i.e. areas of constant grey values.

Must be nonzero at the onset of a gray-level step or ramp discontinuities.

Must be zero along the gray-level ramps of constant slope.

6. The derivative of digital function is defined in terms of difference. Then, which of the following defines the first order derivative ∂f/∂x= ___________ of a one-dimensional function f(x)?

a) f(x+1)-f(x)

b) f(x+1)+ f(x-1)-2f(x)

c) All of the mentioned depending upon the time when partial derivative will be dealt along two spatial axes

d) None of the mentioned

   

Answer: a

Explanation: The definition of a first order derivative of a one dimensional image f(x) is:

∂f/∂x= f(x+1)-f(x), where the partial derivative is used to keep notation same even for f(x, y) when partial derivative will be dealt along two spatial axes.

7. The derivative of digital function is defined in terms of difference. Then, which of the following defines the second order derivative ∂2 f/∂x2 = ___________ of a one-dimensional function f(x)?

a) f(x+1)-f(x)

b) f(x+1)+ f(x-1)-2f(x)

c) All of the mentioned depending upon the time when partial derivative will be dealt along two spatial axes

d) None of the mentioned

   

Answer: b

Explanation: The definition of a second order derivative of a one dimensional image f(x) is:

(∂2 f)/∂x2 =f(x+1)+ f(x-1)-2f(x), where the partial derivative is used to keep notation same even for f(x, y) when partial derivative will be dealt along two spatial axes.

8. What kind of relation can be obtained between first order derivative and second order derivative of an image having a on the basis of edge productions that shows a transition like a ramp of constant slope?

a) First order derivative produces thick edge while second order produces a very fine edge

b) Second order derivative produces thick edge while first order produces a very fine edge

c) Both first and second order produces thick edge

d) Both first and second order produces a very fine edge

   

Answer: a

Explanation: the first order derivative remains nonzero along the entire ramp of constant slope, while the second order derivative remain nonzero only at onset and end of such ramps.

If an edge in an image shows transition like the ramp of constant slope, the first order and second order derivative values shows the production of thick and finer edge respectively.

9. What kind of relation can be obtained between first order derivative and second order derivative of an image on the response obtained by encountering an isolated noise point in the image?

a) First order derivative has a stronger response than a second order

b) Second order derivative has a stronger response than a first order

c) Both enhances the same and so the response is same for both first and second order derivative

d) None of the mentioned

   

Answer: b

Explanation: This is because a second order derivative is more aggressive toward enhancing sharp changes than a first order.

10. What kind of relation can be obtained between the response of first order derivative and second order derivative of an image having a transition into gray-level step from zero?

a) First order derivative has a stronger response than a second order

b) Second order derivative has a stronger response than a first order

c) Both first and second order derivative has the same response

d) None of the mentioned

   

Answer: c

Explanation: This is because a first order derivative has stronger response to a gray-level step than a second order, but, the response becomes same if transition into gray-level step is from zero.

11. If in an image there exist similar change in gray-level values in the image, which of the following shows a stronger response using second order derivative operator for sharpening?

a) A line

b) A step

c) A point

d) None of the mentioned

   

Answer: c

Explanation: second order derivative shows a stronger response to a line than a step and to a point than a line, if there is similar changes in gray-level values in an image.

1. The principle objective of Sharpening, to highlight transitions is ________

a) Pixel density

b) Composure

c) Intensity

d) Brightness

   

Answer: c

Explanation: The principle objective of Sharpening, to highlight transitions is Intensity.

2. How can Sharpening be achieved?

a) Pixel averaging

b) Slicing

c) Correlation

d) None of the mentioned

   

Answer: d

Explanation: Sharpening is achieved using Spatial Differentiation.

3. What does Image Differentiation enhance?

a) Edges

b) Pixel Density

c) Contours

d) None of the mentioned

   

Answer: a

Explanation: Image Differentiation enhances Edges and other discontinuities.

4. What does Image Differentiation de-emphasize?

a) Pixel Density

b) Contours

c) Areas with slowly varying intensities

d) None of the mentioned

   

Answer: c

Explanation: Image Differentiation de-emphasizes areas with slowly varying intensities.

5. The requirements of the First Derivative of a digital function:

a) Must be zero in areas of constant intensity

b) Must be non-zero at the onset of an intensity step

c) Must be non-zero along ramps

d) All of the Mentioned

   

Answer: d

Explanation: All the three conditions must be satisfied.

6. What is the Second Derivative of Image Sharpening called?

a) Gaussian

b) Laplacian

c) Canny

d) None of the mentioned

   

Answer: b

Explanation: It is also called Laplacian.

7. The ability that rotating the image and applying the filter gives the same result, as applying the filter to the image first, and then rotating it, is called _____________

a) Isotropic filtering

b) Laplacian

c) Rotation Invariant

d) None of the mentioned

   

Answer: c

Explanation: It is called Rotation Invariant, although the process used is Isotropic filtering.

8. For a function f(x,y), the gradient of ‘f’ at coordinates (x,y) is defined as a ___________

a) 3-D row vector

b) 3-D column vector

c) 2-D row vector

d) 2-D column vector

   

Answer: d

Explanation: The gradient is a 2-D column vector.

9. Where do you find frequent use of Gradient?

a) Industrial inspection

b) MRI Imaging

c) PET Scan

d) None of the mentioned

   

Answer: a

Explanation: Gradient is used in Industrial inspection, to aid humans, in detection of defects.

10. Which of the following occurs in Unsharp Masking?

a) Blurring original image

b) Adding a mask to original image

c) Subtracting blurred image from original

d) All of the mentioned

   

Answer: d

Explanation: In Unsharp Masking, all of the above occurs in the order: Blurring, Subtracting the blurred image and then Adding the mask.

1. Which of the following make an image difficult to enhance?

a) Narrow range of intensity levels

b) Dynamic range of intensity levels

c) High noise

d) All of the mentioned

   

Answer: d

Explanation: All the mentioned options make it difficult to enhance an image.

2. Which of the following is a second-order derivative operator?

a) Histogram

b) Laplacian

c) Gaussian

d) None of the mentioned

   

Answer: b

Explanation: Laplacian is a second-order derivative operator.

3. Response of the gradient to noise and fine detail is _____________ the Laplacian’s.

a) equal to

b) lower than

c) greater than

d) has no relation with

   

Answer: b

Explanation: Response of the gradient to noise and fine detail is lower than the Laplacian’s and can further be lowered by smoothing.

4. Dark characteristics in an image are better solved using ___________

a) Laplacian Transform

b) Gaussian Transform

c) Histogram Specification

d) Power-law Transformation

   

Answer: d

Explanation: It can be solved by Histogram Specification but it is better handled by Power-law Transformation.

5. What is the smallest possible value of a gradient image?

a) e

b) 1

c) 0

d) -e

   

Answer: c

Explanation: The smallest possible value of a gradient image is 0.

6. Which of the following fails to work on dark intensity distributions?

a) Laplacian Transform

b) Gaussian Transform

c) Histogram Equalization

d) Power-law Transformation

   

Answer: c

Explanation: Histogram Equalization fails to work on dark intensity distributions.

7. _____________ is used to detect diseases such as bone infection and tumors.

a) MRI Scan

b) PET Scan

c) Nuclear Whole Body Scan

d) X-Ray

   

Answer: c

Explanation: Nuclear Whole Body Scan is used to detect diseases such as bone infection and tumors

8. How do you bring out more of the skeletal detail from a Nuclear Whole Body Bone Scan?

a) Sharpening

b) Enhancing

c) Transformation

d) None of the mentioned

   

Answer: a

Explanation: Sharpening is used to bring out more of the skeletal detail.

9. An alternate approach to median filtering is ______________

a) Use a mask

b) Gaussian filter

c) Sharpening

d) Laplacian filter

   

Answer:a

Explanation: Using a mask, formed from the smoothed version of the gradient image, can be used for median filtering.

10. Final step of enhancement lies in _____________ of the sharpened image.

a) Increase range of contrast

b) Increase range of brightness

c) Increase dynamic range

d) None of the mentioned

   

Answer: c

Explanation: Increasing the dynamic range of the sharpened image is the final step in enhancement.

1. What is accepting or rejecting certain frequency components called as?

a) Filtering

b) Eliminating

c) Slicing

d) None of the Mentioned

   

Answer: a

Explanation: Filtering is the process of accepting or rejecting certain frequency components.

2. A filter that passes low frequencies is _____________

a) Band pass filter

b) High pass filter

c) Low pass filter

d) None of the Mentioned

   

Answer: c

Explanation: Low pass filter passes low frequencies.

3. What is the process of moving a filter mask over the image and computing the sum of products at each location called as?

a) Convolution

b) Correlation

c) Linear spatial filtering

d) Non linear spatial filtering

   

Answer: b

Explanation: The process is called as Correlation.

4. The standard deviation controls ___________ of the bell (2-D Gaussian function of bell shape).

a) Size

b) Curve

c) Tightness

d) None of the Mentioned

   

Answer: c

Explanation: The standard deviation controls “tightness” of the bell.

5. What is required to generate an M X N linear spatial filter?

a) MN mask coefficients

b) M+N coordinates

c) MN spatial coefficients

d) None of the Mentioned

   

Answer: a

Explanation: To generate an M X N linear spatial filter MN mask coefficients must be specified.

6. What is the difference between Convolution and Correlation?

a) Image is pre-rotated by 180 degree for Correlation

b) Image is pre-rotated by 180 degree for Convolution

c) Image is pre-rotated by 90 degree for Correlation

d) Image is pre-rotated by 90 degree for Convolution

   

Answer: b

Explanation: Convolution is the same as Correlation except that the image must be rotated by 180 degrees initially.

7. Convolution and Correlation are functions of _____________

a) Distance

b) Time

c) Intensity

d) Displacement

   

Answer: d

Explanation: Convolution and Correlation are functions of displacement.

8. The function that contains a single 1 with the rest being 0s is called ______________

a) Identity function

b) Inverse function

c) Discrete unit impulse

d) None of the Mentioned

   

Answer: c

Explanation: It is called Discrete unit impulse.

9. Which of the following involves Correlation?

a) Matching

b) Key-points

c) Blobs

d) None of the Mentioned.

   

Answer: a

Explanation: Correlation is applied in finding matches.

10. An example of a continuous function of two variables is __________

b) Intensity function

c) Contrast stretching

d) Gaussian function

   

Answer: d

Explanation: Gaussian function has two variables and is an exponential continuous function.

1. The histogram of a digital image with gray levels in the range [0, L-1] is represented by a discrete function:

a) h(r_k)=n_k

b) h(r_k )=n/n_k

c) p(r_k )=n_k

d) h(r_k )=n_k/n

   

Answer: a

Explanation: The histogram of a digital image with gray levels in the range [0, L-1] is a discrete function h(rk )=nk, where rk is the kth gray level and nkis the number of pixels in the image having gray level rk.

2. How is the expression represented for the normalized histogram?

a) p(r_k )=n_k

b) p(r_k )=n_k/n

c) p(r_k)=nn_k

d) p(r_k )=n/n_k

   

Answer: b

Explanation: It is common practice to normalize a histogram by dividing each of its values by the total number of pixels in the image, denoted by n. Thus, a normalized histogram is given by p(rk )=nk/n, for k=0,1,2…..L-1. Loosely speaking, p(rk ) gives an estimate of the probability of occurrence of gray-level rk. Note that the sum of all components of a normalized histogram is equal to 1.

3. Which of the following conditions does the T(r) must satisfy?

a) T(r) is double-valued and monotonically decreasing in the interval 0≤r≤1; and

0≤T(r)≤1 for 0≤r≤1

b) T(r) is double-valued and monotonically increasing in the interval 0≤r≤1; and

0≤T(r)≤1 for 0≤r≤1

c) T(r) is single-valued and monotonically decreasing in the interval 0≤r≤1; and

0≤T(r)≤1 for 0≤r≤1

d) T(r) is single-valued and monotonically increasing in the interval 0≤r≤1; and

0≤T(r)≤1 for 0≤r≤1

   

Answer: d

Explanation: For any r satisfying the aforementioned conditions, we focus attention on transformations of the form

s=T(r) For 0≤r≤1

That produces a level s for every pixel value r in the original image.

For reasons that will become obvious shortly, we assume that the transformation function T(r) satisfies the following conditions:

T(r) is single-valued and monotonically increasing in the interval 0≤r≤1; and

0≤T(r)≤1 for 0≤r≤1.

4. The inverse transformation from s back to r is denoted as:

a) s=T-1(r) for 0≤s≤1

b) r=T-1(s) for 0≤r≤1

c) r=T-1(s) for 0≤s≤1

d) r=T-1(s) for 0≥s≥1

   

Answer: c

Explanation: The inverse transformation from s back to r is denoted by:

r=T-1(s) for 0≤s≤1.

5. The probability density function p_s (s) of the transformed variable s can be obtained by using which of the following formula?

a) p_s (s)=p_r (r)|dr/ds|

b) p_s (s)=p_r (r)|ds/dr|

c) p_r (r)=p_s (s)|dr/ds|

d) p_s (s)=p_r (r)|dr/dr|

   

Answer: a

Explanation: The probability density function p_s (s) of the transformed variable s can be obtained using a basic formula: p_s (s)=p_r (r)|dr/ds|

Thus, the probability density function of the transformed variable, s, is determined by the gray-level PDF of the input image and by the chosen transformation function.

6. A transformation function of particular importance in image processing is represented in which of the following form?

a) s=T(r)=∫0 (2r)pr (ω)dω

b) s=T(r)=∫0 (r-1)pr (ω)dω

c) s=T(r)=∫0 (r/2)pr (ω)dω

d) s=T(r)=∫0 pr (ω)dω

   

Answer: d

Explanation: A transformation function of particular importance in image processing has the form: s=T(r)=∫0 r pr(ω)dw, where ω is a dummy variable of integration. The right side of is recognized as the cumulative distribution function (CDF) of random variable r.

7. Histogram equalization or Histogram linearization is represented by of the following equation:

a) sk =∑k j =1 nj/n k=0,1,2,……,L-1

b) sk =∑k j =0 nj/n k=0,1,2,……,L-1

c) sk =∑k j =0 n/nj k=0,1,2,……,L-1

d) sk =∑k j =n nj/n k=0,1,2,……,L-1

   

Answer: b

Explanation: A plot of pk_ (rk) versus r_k is called a histogram .The transformation (mapping) given in sk =∑k j =0)k nj/n k=0,1,2,……,L-1 is called histogram equalization or histogram linearization.

8. What is the method that is used to generate a processed image that have a specified histogram?

a) Histogram linearization

b) Histogram equalization

c) Histogram matching

d) Histogram processing

   

Answer: c

Explanation: In particular, it is useful sometimes to be able to specify the shape of the histogram that we wish the processed image to have. The method used to generate a processed image that has a specified histogram is called histogram matching or histogram specification.

9. Histograms are the basis for numerous spatial domain processing techniques.

a) True

b) False

   

Answer: a

Explanation: Histograms are the basis for numerous spatial domain processing techniques. Histogram manipulation can be used effectively for image enhancement.

10. In a dark image, the components of histogram are concentrated on which side of the grey scale?

a) High

b) Medium

c) Low

d) Evenly distributed

   

Answer: c

Explanation: We know that in the dark image, the components of histogram are concentrated mostly on the low i.e., dark side of the grey scale. Similarly, the components of histogram of the bright image are biased towards the high side of the grey scale.

1. What is the basis for numerous spatial domain processing techniques?

a) Transformations

b) Scaling

c) Histogram

d) None of the Mentioned

   

Answer: c

Explanation: Histogram is the basis for numerous spatial domain processing techniques.

2. In _______ image we notice that the components of histogram are concentrated on the low side on intensity scale.

a) bright

b) dark

c) colourful

d) All of the Mentioned

   

Answer: b

Explanation: Only in dark images, we notice that the components of histogram are concentrated on the low side on intensity scale.

3. What is Histogram Equalisation also called as?

a) Histogram Matching

b) Image Enhancement

c) Histogram linearisation

d) None of the Mentioned

   

Answer: c

Explanation: Histogram Linearisation is also known as Histogram Equalisation.

4. What is Histogram Matching also called as?

a) Histogram Equalisation

b) Histogram Specification

c) Histogram linearisation

d) None of the Mentioned

   

Answer: b

Explanation: Histogram Specification is also known as Histogram Matching.

5. Histogram Equalisation is mainly used for ________________

a) Image enhancement

b) Blurring

c) Contrast adjustment

d) None of the Mentioned

   

Answer: a

Explanation: It is mainly used for Enhancement of usually dark images.

6. To reduce computation if one utilises non-overlapping regions, it usually produces ______ effect.

a) Dimming

b) Blurred

c) Blocky

d) None of the Mentioned

   

Answer: c

Explanation: Utilising non-overlapping regions usually produces “Blocky” effect.

7. What does SEM stands for?

a) Scanning Electronic Machine

b) Self Electronic Machine

c) Scanning Electron Microscope

d) Scanning Electric Machine

   

Answer: c

Explanation: SEM stands for Scanning Electron Microscope.

8. The type of Histogram Processing in which pixels are modified based on the intensity distribution of the image is called _______________.

a) Intensive

b) Local

c) Global

d) Random

   

Answer: c

Explanation: It is called Global Histogram Processing.

9. Which type of Histogram Processing is suited for minute detailed enhancements?

a) Intensive

b) Local

c) Global

d) Random

   

Answer: b

Explanation: Local Histogram Processing is used.

10. In uniform PDF, the expansion of PDF is ________________

a) Portable Document Format

b) Post Derivation Function

c) Previously Derived Function

d) Probability Density Function

   

Answer: d

Explanation: PDF stands for Probability Density Function

1. The output of a smoothing, linear spatial filtering is a ____________ of the pixels contained in the neighbourhood of the filter mask.

a) Sum

b) Product

c) Average

d) Dot Product

   

Answer: c

Explanation: Smoothing is simply the average of the pixels contained in the neighbourhood.

2. Averaging filters is also known as ____________ filter.

a) Low pass

b) High pass

c) Band pass

d) None of the Mentioned

   

Answer: a

Explanation: Averaging filters is also known as Low pass filters.

3. What is the undesirable side effects of Averaging filters?

a) No side effects

b) Blurred image

c) Blurred edges

d) Loss of sharp transitions

   

Answer: c

Explanation: Blue edges is the undesirable side effect of Averaging filters.

4. A spatial averaging filter in which all coefficients are equal is called _______________.

a) Square filter

b) Neighbourhood

c) Box filter

d) Zero filter

   

Answer: c

Explanation: It is called a Box filter.

5. Which term is used to indicate that pixels are multiplied by different coefficients?

a) Weighted average

b) Squared average

c) Spatial average

d) None of the Mentioned

   

Answer: a

Explanation: It is called weighted average since more importance(weight) is given to some pixels.

6. The non linear spacial filters whose response is based on ordering of the pixels contained is called _____________.

a) Box filter

b) Square filter

c) Gaussian filter

d) Order-statistic filter

   

Answer: d

Explanation: It is called Order-statistic filter.

7. Impulse noise in Order-statistic filter is also called as _______________

a) Median noise

b) Bilinear noise

c) Salt and pepper noise

d) None of the Mentioned

   

Answer: c

Explanation: It is called salt-and-pepper noise because of its appearance as white and black dots superimposed on an image.

8. Best example for a Order-statistic filter is ____________________

a) Impulse filter

b) Averaging filter

c) Median filter

d) None of the Mentioned

   

Answer: c

Explanation: Median filter is the best known Order-statistic filter.

9. What does “eliminated” refer to in median filter?

a) Force to average intensity of neighbours

b) Force to median intensity of neighbours

c) Eliminate median value of pixels

d) None of the Mentioned

   

Answer: b

Explanation: It refers to forcing to median intensity of neighbours.

10. Which of the following is best suited for salt-and-pepper noise elimination?

a) Average filter

b) Box filter

c) Max filter

d) Median filter

   

Answer: d

Explanation: Median filter is better suited than average filter for salt-and-pepper noise elimination.