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The document discusses spatial filtering of images through correlation and convolution. It describes how convolution involves moving a filter kernel over an image and taking the sum of products at each location. Correlation is similar but rotates the kernel 180 degrees. Common linear filters include Gaussian and Sobel filters for smoothing and edge detection. Non-linear filters like median filters can remove noise. The document provides examples of various kernel filters and their applications.

Author

a1719449x

Language

EN