Q. The derivative of digital function is defined in terms of difference. Then, which of the following defines the second order derivative ∂2 f/∂x2 = ___________ of a one-dimensional function f(x)?

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Q. What kind of relation can be obtained between first order derivative and second order derivative of an image having a on the basis of edge productions that shows a transition like a ramp of constant slope?

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Q. What kind of relation can be obtained between first order derivative and second order derivative of an image on the response obtained by encountering an isolated noise point in the image?

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Q. What kind of relation can be obtained between the response of first order derivative and second order derivative of an image having a transition into gray-level step from zero?

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Q. If in an image there exist similar change in gray-level values in the image, which of the following shows a stronger response using second order derivative operator for sharpening?

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Q. The principle objective of Sharpening, to highlight transitions is ________

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Q. How can Sharpening be achieved?

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Q. What does Image Differentiation enhance?

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Q. What does Image Differentiation de-emphasize?

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Q. The requirements of the First Derivative of a digital function:

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Q. What is the Second Derivative of Image Sharpening called?

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Q. The ability that rotating the image and applying the filter gives the same result, as applying the filter to the image first, and then rotating it, is called _____________

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Q. For a function f(x,y), the gradient of ‘f’ at coordinates (x,y) is defined as a ___________

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Q. Where do you find frequent use of Gradient?

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Q. Which of the following occurs in Unsharp Masking?

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Q. Which of the following make an image difficult to enhance?

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Q. Which of the following is a second-order derivative operator?

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Q. Response of the gradient to noise and fine detail is _____________ the Laplacian’s.

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Q. Dark characteristics in an image are better solved using ___________

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Q. What is the smallest possible value of a gradient image?

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