Combining Spatial Enhancement Method MCQ [Free PDF] - Objective Question Answer for Combining Spatial Enhancement Method Quiz

21. What is the basis for numerous spatial domain processing techniques?

A. Transformations
B. Scaling
C. Histogram
D. None of the Mentioned

Answer: C

The histogram is the basis for numerous spatial domain processing techniques.

22. In the _______ image we notice that the components of the histogram are concentrated on the low side of the intensity scale.

A. bright
B. dark
C. colorful
D. All of the Mentioned

Answer: B

Only in dark images, do we notice that the components of the histogram are concentrated on the low side of the intensity scale.

23. What is Histogram Equalisation also called?

A. Histogram Matching
B. Image Enhancement
C. Histogram linearisation
D. None of the Mentioned

Answer: C

Histogram Linearisation is also known as Histogram Equalisation.

24. What is Histogram Matching also called?

A. Histogram Equalisation
B. Histogram Specification
C. Histogram linearisation
D. None of the Mentioned

Answer: B

Histogram Specification is also known as Histogram Matching.

25. Histogram Equalisation is mainly used for ________

A. Image enhancement
B. Blurring
C. Contrast adjustment
D. None of the Mentioned

Answer: A

It is mainly used for the Enhancement of usually dark images.

26. To reduce computation if one utilizes non-overlapping regions, it usually produces the ______ effect.

A. Dimming
B. Blurred
C. Blocky
D. None of the Mentioned

Answer: C

Utilizing non-overlapping regions usually produces a “Blocky” effect.

27. What does SEM stands for?

A. Scanning Electronic Machine
B. Self Electronic Machine
C. Scanning Electron Microscope
D. Scanning Electric Machine

Answer: C

SEM stands for Scanning Electron Microscope.

28. 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

It is called Global Histogram Processing.

29. Which type of Histogram Processing is suited for minutely detailed enhancements?

A. Intensive
B. Local
C. Global
D. Random

Answer: B

Local Histogram Processing is used.

30. 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

PDF stands for Probability Density Function.

31. 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

The histogram of a digital image with gray levels in the range [0, L-1] is a discrete function h(r_k )=n_k, where r_k is the kth gray level and n_kis the number of pixels in the image having a gray level r_k.

32. 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

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(r_k )=n_k/n, for k=0,1,2…..L-1. Loosely speaking, p(r_k ) gives an estimate of the probability of occurrence of gray-level r_k. Note that the sum of all components of a normalized histogram is equal to 1.

33. 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

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.

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