This set of Digital Image Processing Multiple Choice Questions & Answers (MCQs) focuses 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

View Answer

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

View Answer

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

View Answer

Explanation: The process is called as Correlation.

a) Size

b) Curve

c) Tightness

d) None of the Mentioned

View Answer

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

View Answer

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

View Answer

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

View Answer

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

View Answer

Explanation: It is called Discrete unit impulse.

a) Matching

b) Key-points

c) Blobs

d) None of the Mentioned.

View Answer

Explanation: Correlation is applied in finding matches.

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

a) Identity function

b) Intensity function

c) Contrast stretching

d) Gaussian function

View Answer

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

**Sanfoundry Global Education & Learning Series – Digital Image Processing.**

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