Category: Digital Image Processing Objective Questions

250+ TOP MCQs on Combining Spatial Enhancements Methods & Answers

Digital Image Processing Multiple Choice Questions on “Combining Spatial Enhancements Methods”.

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

250+ TOP MCQs on Fundamentals of Spatial Filtering & Answers

Digital Image Processing Multiple Choice Questions on “Fundamentals of Spatial Filtering”.

1. What is accepting or rejecting certain frequency components called as?
A. Filtering
B. Eliminating
C. Slicing
D. None of the Mentioned
Answer: A
Clarification: 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
Clarification: 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
Clarification: 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
Clarification: 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
Clarification: 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
Clarification: 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
Clarification: 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
Clarification: 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
Clarification: 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
Clarification: Gaussian function has two variables and is an exponential continuous function.

250+ TOP MCQs on Histogram Processing – 2 & Answers

Digital Image Processing Interview Questions on “Histogram Processing – 2”.

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
Clarification: 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
Clarification: 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
Clarification: 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
Clarification: 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
Clarification: 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
Clarification: A transformation function of particular importance in image processing has the form: s=T(r)=∫0r 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 =∑kj =1 nj/n k=0,1,2,……,L-1
B. sk =∑kj =0 nj/n k=0,1,2,……,L-1
C. sk =∑kj =0 n/nj k=0,1,2,……,L-1
D. sk =∑kj =n nj/n k=0,1,2,……,L-1
Answer: B
Clarification: A plot of pk_ (rk) versus r_k is called a histogram .The transformation (mapping) given in sk =∑kj =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
Clarification: 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
Clarification: 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
Clarification: 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.

250+ TOP MCQs on Introduction to Digital Image Processing & Answers

Digital Image Processing Multiple Choice Questions on “Introduction to Digital Image Processing”.

1. The spatial coordinates of a digital image (x,y) are proportional to:
A. Position
B. Brightness
C. Contrast
D. Noise
Answer: B
Clarification: The Brightness levels are distributed over the spatial area. Hence, the spatial coordinates are proportional to brightness levels.

2. Among the following image processing techniques which is fast, precise and flexible.
A. Optical
B. Digital
C. Electronic
D. Photographic
Answer: B
Clarification: Digital image processing is more flexible and agile techniques as it is fast, accurate and reliable.

3. An image is considered to be a function of a(x,y), where a represents:
A. Height of image
B. Width of image
C. Amplitude of image
D. Resolution of image
Answer: C
Clarification: The image is a collection of dots with a definite intensity or amplitude.

4. What is pixel?
A. Pixel is the elements of a digital image
B. Pixel is the elements of an analog image
C. Pixel is the cluster of a digital image
D. Pixel is the cluster of an analog image
Answer: A
Clarification: An Image is a collection of individual points referred as pixel, thus a Pixel is the element of a digital image.

5. The range of values spanned by the gray scale is called:
A. Dynamic range
B. Band range
C. Peak range
D. Resolution range
Answer: A
Clarification: The valued spanned in gray scale image are depicted using dynamic range values.

6. Which is a colour attribute that describes a pure colour?
A. Saturation
B. Hue
C. Brightness
D. Intensity
Answer: B
Clarification: The color attribute of an image refers to the contrast of colors, which can be controlled using the Hue values.

7. Which gives a measure of the degree to which a pure colour is diluted by white light?
A. Saturation
B. Hue
C. Intensity
D. Brightness
Answer: A
Clarification: Saturation is color recognizing capability of the human eye. Hence a degree of dilution is measured using saturation.

8. Which means the assigning meaning to a recognized object.
A. Interpretation
B. Recognition
C. Acquisition
D. Segmentation
Answer: A
Clarification: The interpretation is called the assigning meaning to recognized object.

9. A typical size comparable in quality to monochromatic TV image is of size.
A. 256 X 256
B. 512 X 512
C. 1920 X 1080
D. 1080 X 1080
Answer: B
Clarification: A normal T.V have 512 x 512 resolution.

10. The number of grey values are integer powers of:
A. 4
B. 2
C. 8
D. 1
Answer: B
Clarification: The gray values are interpreted as the power of number of colors. In monochromatic image the number of colors are 2.

250+ TOP MCQs on Histogram Processing – 1 & Answers

Digital Image Processing Multiple Choice Questions on “Histogram Processing –
1”.

1. What is the basis for numerous spatial domain processing techniques?
A. Transformations
B. Scaling
C. Histogram
D. None of the Mentioned
Answer: C
Clarification: 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
Clarification: 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
Clarification: 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
Clarification: 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
Clarification: 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
Clarification: 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
Clarification: 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
Clarification: 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
Clarification: 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
Clarification: PDF stands for Probability Density Function.

250+ TOP MCQs on Steps in Image Processing & Answers

Digital Image Processing Multiple Choice Questions on “Steps in Image Processing”.

1. What is the first and foremost step in Image Processing?
A. Image restoration
B. Image enhancement
C. Image acquisition
D. Segmentation
Answer: C
Clarification: Image acquisition is the first process in image processing. Note that acquisition could be as simple as being given an image that is already in digital form. Generally, the image acquisition stage involves preprocessing, such as scaling.

2. In which step of processing, the images are subdivided successively into smaller regions?
A. Image enhancement
B. Image acquisition
C. Segmentation
D. Wavelets
Answer: D
Clarification: Wavelets are the foundation for representing images in various degrees of resolution. Wavelets are particularly used for image data compression and for pyramidal representation, in which images are subdivided successively into smaller regions.

3. What is the next step in image processing after compression?
A. Wavelets
B. Segmentation
C. Representation and description
D. Morphological processing
Answer: D
Clarification: Steps in image processing:
Image acquisition-> Image enhancement-> Image restoration-> Color image processing-> Wavelets and multi resolution processing-> Compression-> Morphological processing-> Segmentation-> Representation & description-> Object recognition.

4. What is the step that is performed before color image processing in image processing?
A. Wavelets and multi resolution processing
B. Image enhancement
C. Image restoration
D. Image acquisition
Answer: C
Clarification: Steps in image processing:
Image acquisition-> Image enhancement-> Image restoration-> Color image processing-> Wavelets and multi resolution processing-> Compression-> Morphological processing-> Segmentation-> Representation & description-> Object recognition.

5. How many number of steps are involved in image processing?
A. 10
B. 9
C. 11
D. 12
Answer: A
Clarification: Steps in image processing:
Image acquisition-> Image enhancement-> Image restoration-> Color image processing-> Wavelets and multi resolution processing-> Compression-> Morphological processing-> Segmentation-> Representation & description-> Object recognition.

6. What is the expanded form of JPEG?
A. Joint Photographic Expansion Group
B. Joint Photographic Experts Group
C. Joint Photographs Expansion Group
D. Joint Photographic Expanded Group
Answer: B
Clarification: Image compression is familiar (perhaps inadvertently) to most users of computers in the form of image file extensions, such as the jpg file extension used in the JPEG (Joint Photographic Experts Group) image compression standard.

7. Which of the following step deals with tools for extracting image components those are useful in the representation and description of shape?
A. Segmentation
B. Representation & description
C. Compression
D. Morphological processing
Answer: D
Clarification: Morphological processing deals with tools for extracting image components that are useful in the representation and description of shape. The material in this chapter begins a transition from processes that output images to processes that output image attributes.

8. In which step of the processing, assigning a label (e.g., “vehicle”) to an object based on its descriptors is done?
A. Object recognition
B. Morphological processing
C. Segmentation
D. Representation & description
Answer: A
Clarification: Recognition is the process that assigns a label (e.g., “vehicle”) to an object based on its descriptors. We conclude our coverage of digital image processing with the development of methods for recognition of individual objects.

9. What role does the segmentation play in image processing?
A. Deals with extracting attributes that result in some quantitative information of interest
B. Deals with techniques for reducing the storage required saving an image, or the bandwidth required transmitting it
C. Deals with partitioning an image into its constituent parts or objects
D. Deals with property in which images are subdivided successively into smaller regions
Answer: C
Clarification: Segmentation procedures partition an image into its constituent parts or objects. In general, autonomous segmentation is one of the most difficult tasks in digital image processing. A rugged segmentation procedure brings the process a long way toward successful solution of imaging problems that require objects to be identified individually.

10. What is the correct sequence of steps in image processing?
A. Image acquisition->Image enhancement->Image restoration->Color image processing->Compression->Wavelets and multi resolution processing->Morphological processing->Segmentation->Representation & description->Object recognition
B. Image acquisition->Image enhancement->Image restoration->Color image processing->Wavelets and multi resolution processing->Compression->Morphological processing->Segmentation->Representation & description->Object recognition
C. Image acquisition->Image enhancement->Color image processing->Image restoration->Wavelets and multi resolution processing->Compression->Morphological processing->Segmentation->Representation & description->Object recognition
D. Image acquisition->Image enhancement->Image restoration->Color image processing->Wavelets and multi resolution processing->Compression->Morphological processing->Representation & description->Segmentation->Object recognition
Answer: B
Clarification: Steps in image processing:
Image acquisition-> Image enhancement->Image restoration->Color image processing->Wavelets and multi resolution processing->Compression->Morphological processing->Segmentation->Representation & description->Object recognition.