# Histogram Equalization MCQ [Free PDF] – Objective Question Answer for Histogram Equalization Quiz

1. If h(rk) = nk, rk the kth gray level and nk total pixels with gray level rk, is a histogram in the gray level range [0, L – 1]. Then how can we normalize a histogram?

A. If each value of the histogram is added by the total number of pixels in the image, say n, p(RK)=nk+n
B. If each value of the histogram is subtracted by the total number of pixels in the image, say n, p(rk)=nk-n
C. If each value of the histogram is multiplied by the total number of pixels in the image, say n, p(rk)=nk * n
D. If each value of the histogram is divided by the total number of pixels in the image, say n, p(rk)=nk / n

To normalize a histogram each of its values is divided by a total number of pixels in the image, say n. p(rk) = nk / n.

2. What is the sum of all components of a normalized histogram?

A. 1
B. -1
C. 0
D. None of the mentioned

A normalized histogram. p(rk) = nk / n
Where n is the total number of pixels in the image, rk is the kth gray level and nk total pixels with gray level rk.
Here, p(rk) gives the probability of occurrence of rk.

3. A low contrast image will have what kind of histogram when, the histogram, h(rk) = nk, rk the kth gray level and nk total pixels with gray level rk, is plotted nk versus rk?

A. The histogram that is concentrated on the dark side of the grayscale
B. The histogram whose components are biased toward the high side of the grayscale
C. The histogram that is narrow and centered toward the middle of the grayscale
D. The histogram that covers a wide range of grayscale and the distribution of pixels is approximately uniform

The histogram plot is nk versus rk. So, the histogram of a low contrast image will be narrow and centered toward the middle of the gray scale.
A dark image will have a histogram that is concentrated on the dark side of the gray scale.

A bright image will have the histogram whose components are biased toward the high side of the gray scale.
A high contrast image will have a histogram that covers a wide range of gray scales and the distribution opixelsel is approximately uniform.

4. A bright image will have what kind of histogram, when the histogram, h(rk) = nk, rk the kth gray level and nk total pixels with gray level rk, is plotted nk versus rk?

A. The histogram that is concentrated on the dark side of the gray scale
B. The histogram whose components are biased toward the high side of the gray scale
C. The histogram that is narrow and centered toward the middle of the gray scale
D. The histogram that covers a wide range of gray scales and the distribution of pixels is approximately uniform

The histogram plot is nk versus rk. So, the histogram of a low contrast image will be narrow and centered toward the middle of the gray scale.
A dark image will have a histogram that is concentrated on the dark side of the gray scale.

A bright image will have the histogram whose components are biased toward the high side of the gray scale.
A high contrast image will have a histogram that covers a wide range of gray scales and the distribution of pixels is approximately uniform.

5. A high contrast image and a dark image will have what kind of histogram respectively, when the histogram, h(rk) = nk, rk the kth gray level and nk total pixels with gray level rk, is plotted nk versus rk?
The histogram is concentrated on the dark side of the gray scale.
The histogram whose components are biased toward the high side of the gray scale.
The histogram is narrow and centered toward the middle of the gray scale.
The histogram covers a wide range of gray scales and the distribution of pixels is approximately uniform.

A. I) And II) respectively
B. III) And II) respectively
C. II) And IV) respectively
D. IV) And I) respectively

The histogram plot is nk versus rk. So, the histogram of a low contrast image will be narrow and centered toward the middle of the gray scale.
A dark image will have a histogram that is concentrated on the dark side of the gray scale.

A bright image will have the histogram whose components are biased toward the high side of the gray scale.
A high contrast image will have a histogram that covers a wide range of gray scales and the distribution of pixels is approximately uniform.

6. The transformation s = T(r) produces a gray level s for each pixel valuer of the input image. Then, if the T(r) is single-valued in interval 0 ≤ r ≤ 1, what does it signifies?

A. It guarantees the existence of inverse transformation
B. It is needed to restrict producing of some inverted gray levels in the output
C. It guarantees that the output gray level and the input gray level will be in the same range
D. All of the mentioned

The T(r) is single-valued in interval 0 ≤ r ≤ 1, which guarantees the existence of inverse transformation.

7. The transformation s = T(r) produces a gray level s for each pixel valuer of the input image. Then, if the T(r) is monotonically increasing in interval 0 ≤ r ≤ 1, what does it signifies?

A. It guarantees the existence of inverse transformation
B. It is needed to restrict producing of some inverted gray levels in the output
C. It guarantees that the output gray level and the input gray level will be in the same range
D. All of the mentioned

A T(r) that is not monotonically increasing, could result in an output containing at least a section of inverted intensity range. The T(r) is monotonically increasing in interval 0 ≤ r ≤ 1, which is needed to restrict producing of some inverted gray levels in output.

8. The transformation s = T(r) produces a gray level s for each pixel valuer of the input image. Then, if the T(r) is satisfying 0 ≤ T(r) ≤ 1 in interval 0 ≤ r ≤ 1, what does it signifies?

A. It guarantees the existence of inverse transformation
B. It is needed to restrict producing of some inverted gray levels in the output
C. It guarantees that the output gray level and the input gray level will be in the same range
D. All of the mentioned

If, 0 ≤ T(r) ≤ 1 in interval 0 ≤ r ≤ 1, then the output gray level and the input gray level will be in the same range.

9. What is the full form for PDF, a fundamental descriptor of random variables i.e. gray values in an image?

A. Pixel distribution function
B. Portable document format
C. Pel deriving function
D. Probability density function

For a random variable, a PDF, the probability density function, is one of the most fundamental descriptors.

10. What is the full form of CDF?

A. Cumulative density function
B. Contour derived function
C. Cumulative distribution function
D. None of the mentioned