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If I make a mistake and use cross - correlation instead of convolution when computing 2 D gradient vectors of an image using the central
If I make a mistake and use crosscorrelation instead of convolution when computing D gradient vectors of an image using the central finite difference filter the computed values of my gradient vectors will not necessarily be correct. Answer the following TrueFalse questions. Ignore border pixels, only think about pixels in the interior of the image. Hint: to answer these questions, think first about the numeric effects of applying this specific filter differently, then think about what implications the different values have when interpreted geometrically as the gradient of an intensity surface.
a Thecomputedgradientvectorwillpointintheoppositedirectionegdownhillinstead of uphillT or F
b The computed gradient vector will be perpendicular to the correct gradient. T or F
c The computed gradient will still be at local minima maxima in the image. T of Fd The magnitude length of the computed gradient vector will still be correct. T or F
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