# Spatial Filtering MCQ [Free PDF] – Objective Question Answer for Spatial Filtering Quiz

1. In neighborhood operations working is being done with the value of the image pixel in the neighborhood and the corresponding value of a sub-image that has the same dimension as the neighborhood. The sub-image is referred as _________

A. Filter
B. Mask
C. Template
D. All of the mentioned

Answer: D

Working in neighborhood operations is done with the value of a sub-image having the same dimension as the neighborhood corresponding to the value in the image pixel. The sub-image is called a filter, mask, template, kernel, or window.

2. The response for linear spatial filtering is given by the relationship __________

A. Sum of filter coefficient’s product and corresponding image pixel under filter mask
B. Difference of filter coefficient’s product and corresponding image pixel under filter mask
C. Product of filter coefficient’s product and corresponding image pixel under filter mask
D. None of the mentioned

Answer: A

In spatial filtering, the mask is moved from point to point and at each point, the response is calculated using a predefined relationship. The relationship is linear spatial filtering is given by: the Sum of the filter coefficient’s product and the corresponding image pixel in an area under the filter mask.

3. In linear spatial filtering, what is the pixel of the image under mask corresponding to the mask coefficient w (1, -1), assuming a 3*3 mask?

A. f (x, -y)
B. f (x + 1, y)
C. f (x, y – 1)
D. f (x + 1, y – 1)

Answer: D

The pixel corresponding to mask coefficient (a 3*3 mask) w (0, 0) is f (x, y), and so for w (1, -1) is f (x + 1, y – 1).

4. Which of the following is/are a nonlinear operation?

A. Computation of variance
B. Computation of median
C. All of the mentioned
D. None of the mentioned

Answer: C

Computation of variance, as well as median, comes under nonlinear operation.

5. Which of the following is/are used as a basic function in a nonlinear filter for noise reduction?

A. Computation of variance
B. Computation of median
C. All of the mentioned
D. None of the mentioned

Answer: B

The computation of the median gray-level value in the neighborhood is the basic function of a nonlinear filter for noise reduction.

6. In neighborhood operation for spatial filtering if a square mask of size n*n is used it is restricted that the center of the mask must be at a distance ≥ (n – 1)/2 pixels from the border of the image, what happens to the resultant image?

A. The resultant image will be of the same size as the original image
B. The resultant image will be a little larger size than the original image
C. The resultant image will be a little smaller size than the original image
D. None of the mentioned

Answer: C

If the center of the mask must be at a distance ≥ (n – 1)/2 pixels from the border of the image, the border pixels won’t get processed under the mask and so the resultant image would be of smaller size.

7. Which of the following method is/are used for padding the image?

A. Adding rows and columns of 0 or other constant gray levels
B. Simply replicating the rows or columns
C. All of the mentioned
D. None of the mentioned

Answer: C

In neighborhood operation for spatial filtering using the square mask, padding of the original image is done to obtain a filtered image of the same size as of original image done, by adding rows and columns of 0 or other constant gray level or by replicating the rows or columns of the original image.

8. In neighborhood operation for spatial filtering using a square mask of n*n, which of the following approach is/are used to obtain a perfectly filtered result irrespective of the size?

A. By padding the image
B. By filtering all the pixels only with the mask section that is fully contained in the image
C. By ensuring that the center of the mask must be at a distance ≥ (n – 1)/2 pixels from the border of the image
D. None of the mentioned

Answer: C

By ensuring that the center of the mask must be at a distance ≥ (n – 1)/2 pixels from the border of the image, the resultant image would be of smaller size but all the pixels would be the result of the filter processing and so is a fully filtered result.

In the other approach, padding affects the values near the edges that get more prevalent with mask size increase, while another approach results in the band of pixels near the border that gets processed with a partial filter mask. So, not a fully filtered case.

9. Which of the following fact(s) is/are true for the relationship between the low-frequency component of Fourier transform and the rate of change of gray levels?

A. Moving away from the origin of transform the low frequency corresponds to smooth gray level variation
B. Moving away from the origin of transformation the low frequencies correspond to an abrupt change in gray level
C. All of the mentioned
D. None of the mentioned

Answer: C

Moving away from the origin of transform the low frequency corresponds to the slowly varying components in an image. Moving further away from origin the higher frequencies corresponds to faster gray level changes.

10. Which of the following fact(s) is/are true for the relationship between the high-frequency component of Fourier transform and the rate of change of gray levels?

A. Moving away from the origin of transform the high frequency corresponds to smooth gray level variation
B. Moving away from the origin of transformation the higher frequencies correspond to an abrupt change in gray level
C. All of the mentioned
D. None of the mentioned

Answer: B

Moving away from the origin of transform the low frequency corresponds to the slowly varying components in an image. Moving further away from origin the higher frequencies corresponds to faster gray level changes.

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