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The standard deviation ‘σ’ at any point in image averaging:
A filter is applied to an image whose response is independent of the direction of discontinuities in the image. The filter is/are ________
In isotropic filtering, which of the following is/are the simplest isotropic derivative operator?
The Laplacian is which of the following operator?
The Laplacian ∇^2 f=[f(x + 1, y) + f(x – 1, y) + f(x, y + 1) + f(x, y – 1) – 4f(x, y)], gives an isotropic result for rotations in increment by what degree?
The Laplacian incorporated with diagonal directions, i.e. ∇^2 f=[f(x + 1, y) + f(x – 1, y) + f(x, y + 1) + f(x, y – 1) – 8f(x, y)], gives an isotropic result for rotations in increment by what degree?
Applying Laplacian has which of the following result(s)?
Applying Laplacian produces image having featureless background which is recovered maintaining the sharpness of Laplacian operation by either adding or subtracting it from the original image depending upon the Laplacian definition used. Which of the following is true based on above statement?
A mask of size 3*3 is formed using Laplacian including diagonal neighbors that has central coefficient as 9. Then, what would be the central coefficient of same mask if it is made without diagonal neighbors?
Which of the following mask(s) is/are used to sharpen images by subtracting a blurred version of original image from the original image itself?
Which of the following gives an expression for high boost filtered image fhb,
If we use a Laplacian to obtain sharp image for unsharp mask filtered image fs(x, y) of f(x, y) as input image
“For very large value of A, a high boost filtered image is approximately equal to the original image”. State whether the statement is true or false?
Subtracting Laplacian from an image is proportional to which of the following?
A First derivative in image processing is implemented using which of the following given operator(s)?
What is the sum of the coefficient of the mask defined using gradient?
Gradient is used in which of the following area(s)?
Gradient have some important features. Which of the following is/are some of them?
An image has significant edge details. Which of the following fact(s) is/are true for the gradient image and the Laplacian image of the same?
The Laplacian in frequency domain is simply implemented by using filter __________
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