Digital Image Processing Histogram Equalization Online Exam Quiz
Digital Image Processing Histogram Equalization GK Quiz. Question and Answers related to Digital Image Processing Histogram Equalization. MCQ (Multiple Choice Questions with answers about Digital Image Processing Histogram Equalization
What is the sum of all components of a normalized histogram?
Options
A : 1
B : -1
C : 0
D : None of the mentioned
What is the full form of CDF?
Options
A : Cumulative density function
B : Contour derived function
C : Cumulative distribution function
D : None of the mentioned
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 _______
Options
A : Histogram linearization
B : Histogram equalization
C : All of the mentioned
D : None of the mentioned
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?
Options
A : If each value of histogram is added by total number of pixels in image, say n, p(rk)=nk+n
B : If each value of histogram is subtracted by total number of pixels in image, say n, p(rk)=nk-n
C : If each value of histogram is multiplied by total number of pixels in image, say n, p(rk)=nk * n
D : If each value of histogram is divided by total number of pixels in image, say n, p(rk)=nk / n
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?
Options
A : It guarantees the existence of inverse transformation
B : It is needed to restrict producing of some inverted gray levels in output
C : It guarantees that the output gray level and the input gray level will be in same range
D : All of the mentioned
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?
Options
A : It guarantees the existence of inverse transformation
B : It is needed to restrict producing of some inverted gray levels in output
C : It guarantees that the output gray level and the input gray level will be in same range
D : All of the mentioned
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?
Options
A : It guarantees the existence of inverse transformation
B : It is needed to restrict producing of some inverted gray levels in output
C : It guarantees that the output gray level and the input gray level will be in same range
D : All of the mentioned
What is the full form for PDF, a fundamental descriptor of random variables i.e. gray values in an image?
Options
A : Pixel distribution function
B : Portable document format
C : Pel deriving function
D : Probability density function
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 __________
Options
A : Single valued
B : Monotonically increasing
C : All of the mentioned
D : None of the mentioned
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?
Options
A : The histogram that are concentrated on the dark side of gray scale
B : The histogram whose component are biased toward high side of gray scale
C : The histogram that is narrow and centered toward the middle of gray scale
D : The histogram that covers wide range of gray scale and the distribution of pixel is approximately uniform
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