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

tIt guarantees the existence of inverse transformation

tIt is needed to restrict producing of some inverted gray levels in output

tIt guarantees that the output gray level and the input gray level will be in same range

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

tIt guarantees that the output gray level and the input gray level will be in same range

tIt guarantees the existence of inverse transformation

tIt is needed to restrict producing of some inverted gray levels in output

tIt guarantees that the output gray level and the input gray level will be in same range

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

tIt is needed to restrict producing of some inverted gray levels in output

tIt guarantees the existence of inverse transformation

tIt is needed to restrict producing of some inverted gray levels in output

tIt guarantees that the output gray level and the input gray level will be in same range

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?

tThe histogram that is narrow and centered toward the middle of gray scale

tThe histogram that are concentrated on the dark side of gray scale

tThe histogram whose component are biased toward high side of gray scale

tThe histogram that is narrow and centered toward the middle of gray scale

tThe histogram that covers wide range of gray scale and the distribution of pixel is approximately uniform

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

tIf each value of histogram is added by total number of pixels in image, say n, p(rk)=nk+n

If each value of histogram is subtracted by total number of pixels in image, say n, p(rk)=nk-n

tIf each value of histogram is multiplied by total number of pixels in image, say n, p(rk)=nk * n

tIf each value of histogram is divided by total number of pixels in image, say n, p(rk)=nk / n

7 + Mcqs in Histogram Equalization and Processing in Digital Image Processing Page 1 McqOptions

1.	The transformation T (r_k) = ^k_(j=0) nj /n, k = 0, 1, 2, , L-1, where L is max gray value possible and r-k is the kth gray level, is called _______
A.	tHistogram linearization
B.	tHistogram equalization
C.	tAll of the mentioned
D.	tNone of the mentioned
Answer» D. tNone of the mentioned

Discussion

2.	For the transformation T(r) = [ ₀^r pr(w) dw], r is gray value of input image, pr(r) is PDF of random variable r and w is a dummy variable. If, the PDF are always positive and that the function under integral gives the area under the function, the transformation is said to be __________
A.	tSingle valued
B.	tMonotonically increasing
C.	tAll of the mentioned
D.	tNone of the mentioned
Answer» D. tNone of the mentioned

Discussion

3.	The transformation s = T(r) producing a gray level s for each pixel value r of input image. Then, if the T(r) is satisfying 0 T(r) 1 in interval 0 r 1, what does it signifies?
A.	tIt guarantees the existence of inverse transformation
B.	tIt is needed to restrict producing of some inverted gray levels in output
C.	tIt guarantees that the output gray level and the input gray level will be in same range
D.	tAll of the mentioned
Answer» D. tAll of the mentioned

Discussion

4.	The transformation s = T(r) producing a gray level s for each pixel value r of input image. Then, if the T(r) is monotonically increasing in interval 0 r 1, what does it signifies?
A.	tIt guarantees the existence of inverse transformation
B.	tIt is needed to restrict producing of some inverted gray levels in output
C.	tIt guarantees that the output gray level and the input gray level will be in same range
D.	tAll of the mentioned
Answer» C. tIt guarantees that the output gray level and the input gray level will be in same range

Discussion

5.	The transformation s = T(r) producing a gray level s for each pixel value r of input image. Then, if the T(r) is single valued in interval 0 r 1, what does it signifies?
A.	tIt guarantees the existence of inverse transformation
B.	tIt is needed to restrict producing of some inverted gray levels in output
C.	tIt guarantees that the output gray level and the input gray level will be in same range
D.	tAll of the mentioned
Answer» B. tIt is needed to restrict producing of some inverted gray levels in output

Discussion

6.	A bright image will have what kind of histogram, when the histogram, h(r_k) = n_k, r_k the kth gray level and n_k total pixels with gray level r_k, is plotted n_k versus r_k?
A.	tThe histogram that are concentrated on the dar<sub>k</sub> side of gray scale
B.	tThe histogram whose component are biased toward high side of gray scale
C.	tThe histogram that is narrow and centered toward the middle of gray scale
D.	tThe histogram that covers wide range of gray scale and the distribution of pixel is approximately uniform
Answer» C. tThe histogram that is narrow and centered toward the middle of gray scale

Discussion

7.	If h(r_k) = n_k, r_k the kth gray level and n_k total pixels with gray level r_k, is a histogram in gray level range [0, L 1]. Then how can we normalize a histogram?
A.	tIf each value of histogram is added by total number of pixels in image, say n, p(r<sub>k</sub>)=n<sub>k</sub>+n
B.	If each value of histogram is subtracted by total number of pixels in image, say n, p(r<sub>k</sub>)=n<sub>k</sub>-n
C.	tIf each value of histogram is multiplied by total number of pixels in image, say n, p(r<sub>k</sub>)=n<sub>k</sub> * n
D.	tIf each value of histogram is divided by total number of pixels in image, say n, p(r<sub>k</sub>)=n<sub>k</sub> / n
Answer» E.

Discussion

Explore topic-wise MCQs in Digital Image Processing.

The transformation T (rk) = k(j=0) nj /n, k = 0, 1, 2, , L-1, where L is max gray value possible and r-k is the kth gray level, is called _______

For the transformation T(r) = [ 0r pr(w) dw], r is gray value of input image, pr(r) is PDF of random variable r and w is a dummy variable. If, the PDF are always positive and that the function under integral gives the area under the function, the transformation is said to be __________

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

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

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

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?

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

The transformation T (r_k) = ^k_(j=0) nj /n, k = 0, 1, 2, , L-1, where L is max gray value possible and r-k is the kth gray level, is called _______

For the transformation T(r) = [ ₀^r pr(w) dw], r is gray value of input image, pr(r) is PDF of random variable r and w is a dummy variable. If, the PDF are always positive and that the function under integral gives the area under the function, the transformation is said to be __________

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

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