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This article will explain in detail the example analysis of differential processing based on matlab image center. The editor thinks it is very practical, so I share it with you for reference. I hope you can get something after reading this article.

When processing images, especially when dealing with video stream images, the method of image difference is often used. As the name implies, image difference is to subtract the corresponding pixel values of two images to weaken the similar part of the image and highlight the changing part of the image. For example, the differential image can often detect the outline of the moving target, extract the trajectory of the flicker tube and so on.

Central differential source code:

I = imread ('lena1.png'); figure; imshow (I); forward_dx = mipforwarddiff (Idx'); figure, imshow (forward_dx); forward_dy = mipforwarddiff (Iddy'); figure, imshow (forward_dy); central_dx = mipcentraldiff (Idx'); figure, imshow (central_dx); central_dy = mipcentraldiff (Iddy'); figure, imshow (central_dy) Function dimg = mipcentraldiff (img,direction)% MIPCENTRALDIFF Finite difference calculations% DIMG = MIPCENTRALDIFF (IMG,DIRECTION)% Calculates the central-difference for a given direction% IMG: input image% DIRECTION: 'dx' or' dy'% DIMG: resultant image%img = padarray (img, [11], 'symmetric','both'); [row,col] = size (img); dimg = zeros (row,col) Switch (direction) case 'dx', dimg (:, 2:col-1) = (img (:, 3:col)-img (:, 1:col-2)) / 2; case' dy', dimg (2dx', dimg:)) = (img (3Rowley:)-img (1GRV Rowlinger:)) / 2; otherwise, disp ('Direction is unknown'); enddimg = dimg (2RV endly1)

Original drawing

X direction

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