Intensity Transformation MCQ [Free PDF] – Objective Question Answer for Intensity Transformation Quiz

61. Which of the following makes 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

The following options make an image difficult to enhance

  • The narrow range of intensity levels
  • The dynamic range of intensity levels
  • High noise

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

 

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

A. Histogram
B. Laplacian
C. Gaussian
D. None of the mentioned

Answer: B

Laplacian is a second-order derivative operator.

 

63. Response of the gradient to noise and fine detail is _________ the Laplacians.

A. equal to
B. lower than
C. greater than
D. has no relation with

Answer: B

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

 

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

A. Laplacian Transform
B. Gaussian Transform
C. Histogram Specification
D. Power-law Transformation

Answer: D

Dark characteristics in an image are better solved using Power-law Transformation.

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

 

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

A. e
B. 1
C. 0
D. -e

Answer: C

The smallest possible value of a gradient image is 0.

 

66. 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

Histogram Equalization fails to work on dark intensity distributions.

 

67. _____________ 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

A nuclear Whole Body Scan is used to detect diseases such as bone infection and tumors.

 

68. 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

Sharpening is used to bring out more of the skeletal detail from a Nuclear whole Body Bone Scan.

 

69. An alternate approach to median filtering is _________

A. Use a mask
B. Gaussian filter
C. Sharpening
D. Laplacian filter

Answer: A

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

 

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

A. Increase the range of contrast
B. Increase the range of brightness
C. Increase dynamic range
D. None of the mentioned

Answer: C

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

 

71. What is accepting or rejecting certain frequency components called?

A. Filtering
B. Eliminating
C. Slicing
D. None of the Mentioned

Answer: A

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

 

72. A filter that passes low frequencies is _____________

A. Bandpass filter
B. High pass filter
C. Low pass filter
D. None of the Mentioned

Answer: C

The low pass filter passes low frequencies.

 

73. 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

The process of moving a filter mask over the image and computing the sum of products at each location is called Correlation.

 

74. 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

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

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

 

75. 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

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

 

76. What is the difference between Convolution and Correlation?

A. Image is pre-rotated by 180 degrees for Correlation
B. Image is pre-rotated by 180 degrees for Convolution
C. Image is pre-rotated by 90 degrees for Correlation
D. Image is pre-rotated by 90 degrees for Convolution

Answer: B

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

 

77. Convolution and Correlation are functions of __________

A. Distance
B. Time
C. Intensity
D. Displacement

Answer: D

Convolution and Correlation are functions of displacement.

Convolution is the calculation of the area under the product of two signals in LTI systems whereas correlation is a measurement of similarity between two signals.

Correlation is a measurement of the similarity between two signals/sequences. Convolution is the measurement of the effect of one signal on the other signal.

 

78. 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

The function that contains a single 1 with the rest being 0s is called Discrete unit impulse.

 

79. Which of the following involves Correlation?

A. Matching
B. Key-points
C. Blobs
D. None of the Mentioned.

Answer: A

Correlation is applied in finding matches. Correlation is the process of moving a filter mask often referred to as kernel over the image and computing the sum of products at each location. Correlation is the function of displacement of the filter.

 

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

A. Identity function
B. Intensity function
C. Contrast stretching
D. Gaussian function

Answer: D

The Gaussian function has two variables and is an exponential continuous function.

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