Category: Digital Image Processing Objective Questions

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.

250+ TOP MCQs on Smoothing Spacial Filters & Answers

Digital Image Processing Multiple Choice Questions on “Smoothing Spacial Filters”.

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

250+ TOP MCQs on Basics Of Image Sampling & Quantization & Answers

Digital Image Processing Multiple Choice Questions & Answers on “Basics Of Image Sampling & Quantization”.

1. To convert a continuous sensed data into Digital form, which of the following is required?
A. Sampling
B. Quantization
C. Both Sampling and Quantization
D. Neither Sampling nor Quantization

Answer: C
Clarification: The output of the most sensor is a continuous waveform and the amplitude and spatial behavior of such waveform are related to the physical phenomenon being sensed.

2. To convert a continuous image f(x, y) to digital form, we have to sample the function in __________
A. Coordinates
B. Amplitude`
C. All of the mentioned
D. None of the mentioned

Answer: C
Clarification: An image may be continuous in the x- and y-coordinates or in amplitude, or in both.

3. For a continuous image f(x, y), how could be Sampling defined?
A. Digitizing the coordinate values
B. Digitizing the amplitude values
C. All of the mentioned
D. None of the mentioned

Answer: A
Clarification: Sampling is the method of digitizing the coordinate values of the image.

4. For a continuous image f(x, y), Quantization is defined as
A. Digitizing the coordinate values
B. Digitizing the amplitude values
C. All of the mentioned
D. None of the mentioned

Answer: B
Clarification: Sampling is the method of digitizing the amplitude values of the image.

5. Validate the statement:
“For a given image in one-dimension given by function f(x, y), to sample the function we take equally spaced samples, superimposed on the function, along a horizontal line. However, the sample values still span (vertically) a continuous range of gray-level values. So, to convert the given function into a digital function, the gray-level values must be divided into various discrete levels.”
A. True
B. False

Answer: A
Clarification: Digital function requires both sampling and quantization of the one-dimensional image function.

6. How is sampling been done when an image is generated by a single sensing element combined with mechanical motion?
A. The number of sensors in the strip defines the sampling limitations in one direction and Mechanical motion in the other direction.
B. The number of sensors in the sensing array establishes the limits of sampling in both directions.
C. The number of mechanical increments when the sensor is activated to collect data.
D. None of the mentioned.

Answer: C
Clarification: When an image is generated by a single sensing element along with mechanical motion, the output data is quantized by dividing the gray-level scale into many discrete levels. However, sampling is done by selecting the number of individual mechanical increments recorded at which we activate the sensor to collect data.

7. How does sampling gets accomplished with a sensing strip being used for image acquisition?
A. The number of sensors in the strip establishes the sampling limitations in one image direction and Mechanical motion in the other direction
B. The number of sensors in the sensing array establishes the limits of sampling in both directions
C. The number of mechanical increments when the sensor is activated to collect data
D. None of the mentioned

Answer: A
Clarification: When a sensing strip is used the number of sensors in the strip defines the sampling limitations in one direction and mechanical motion in the other direction.

8. How is sampling accomplished when a sensing array is used for image acquisition?
A. The number of sensors in the strip establishes the sampling limitations in one image direction and Mechanical motion in the other direction
B. The number of sensors in the sensing array defines the limits of sampling in both directions
C. The number of mechanical increments at which we activate the sensor to collect data
D. None of the mentioned

Answer: B
Clarification: When we use sensing array for image acquisition, there is no motion and so, only the number of sensors in the array defines the limits of sampling in both directions and the output of the sensor is quantized by dividing the gray-level scale into many discrete levels.

9. The quality of a digital image is well determined by ___________
A. The number of samples
B. The discrete gray levels
C. All of the mentioned
D. None of the mentioned

Answer: C
Clarification: The quality of a digital image is determined mostly by the number of samples and discrete gray levels used in sampling and quantization.

250+ TOP MCQs on Smoothing Linear Spatial Filters & Answers

Digital Image Processing Questions and Answers for Aptitude test on “Smoothing Linear Spatial Filters”.

1. Smoothing filter is used for which of the following work(s)?
A. Blurring
B. Noise reduction
C. All of the mentioned
D. None of the mentioned
Answer: C
Clarification: Smoothing filter is used for blurring and noise reduction.

2. The response of the smoothing linear spatial filter is/are __________
A. Sum of image pixel in the neighborhood filter mask
B. Difference of image in the neighborhood filter mask
C. Product of pixel in the neighborhood filter mask
D. Average of pixels in the neighborhood of filter mask
Answer: D
Clarification: The average of pixels in the neighborhood of filter mask is simply the output of the smoothing linear spatial filter.

3. Which of the following filter(s) results in a value as average of pixels in the neighborhood of filter mask.
A. Smoothing linear spatial filter
B. Averaging filter
C. Lowpass filter
D. All of the mentioned
Answer: D
Clarification: The output as an average of pixels in the neighborhood of filter mask is simply the output of the smoothing linear spatial filter also known as averaging filter and lowpass filter.

4. What is/are the resultant image of a smoothing filter?
A. Image with high sharp transitions in gray levels
B. Image with reduced sharp transitions in gray levels
C. All of the mentioned
D. None of the mentioned
Answer: B
Clarification: Random noise has sharp transitions in gray levels and smoothing filters does noise reduction.

5. At which of the following scenarios averaging filters is/are used?
A. In the reduction of irrelevant details in an image
B. For smoothing of false contours
C. For noise reductions
D. All of the mentioned
Answer: D
Clarification: Averaging filter or smoothing linear spatial filter is used: for noise reduction by reducing the sharp transitions in gray level, for smoothing false contours that arises because of use of insufficient number of gray values and for reduction of irrelevant data i.e. the pixels regions that are small in comparison of filter mask.

6. A spatial averaging filter having all the coefficients equal is termed _________
A. A box filter
B. A weighted average filter
C. A standard average filter
D. A median filter
Answer: A
Clarification: An averaging filter is termed as box filter if all the coefficients of spatial averaging filter are equal.

7. What does using a mask having central coefficient maximum and then the coefficients reducing as a function of increasing distance from origin results?
A. It results in increasing blurring in smoothing process
B. It results to reduce blurring in smoothing process
C. Nothing with blurring occurs as mask coefficient relation has no effect on smoothing process
D. None of the mentioned
Answer: A
Clarification: Use of a mask having central coefficient maximum and then the coefficients reducing as a function of increasing distance from origin is a strategy to reduce blurring in smoothing process.

8. What is the relation between blurring effect with change in filter size?
A. Blurring increases with decrease of the size of filter size
B. Blurring decrease with decrease of the size of filter size
C. Blurring decrease with increase of the size of filter size
D. Blurring increases with increase of the size of filter size
Answer: D
Clarification: Using a size 3 filter 3*3 and 5*5 size squares and other objects shows a significant blurring with respect to object of larger size.
The blurring gets more pronounced while using filter size 5, 9 and so on.

of Digital Image Processing for Aptitude test,