First-derivative gradient operators are the foundation of edge detection. Sobel is the workhorse, Scharr offers slightly better rotational symmetry, Prewitt is a simpler unweighted alternative, and Laplacian is a second-derivative operator highlighting zero-crossings. This card lets you compare all four with controllable kernel size, direction, and strength.
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Compare first-derivative Sobel, Scharr, and Prewitt operators with the second-derivative Laplacian operator. The output visualizes intensity changes selected by the operator and direction controls.