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[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2023-10-06 UTC."],[[["\u003cp\u003eCreates a 3x3 kernel for edge detection using the Laplacian-4 operator.\u003c/p\u003e\n"],["\u003cp\u003eThe kernel can be scaled using the \u003ccode\u003emagnitude\u003c/code\u003e argument and normalized using the \u003ccode\u003enormalize\u003c/code\u003e argument.\u003c/p\u003e\n"],["\u003cp\u003eThe default kernel values are: \u003ccode\u003e[[0, 1, 0], [1, -4, 1], [0, 1, 0]]\u003c/code\u003e.\u003c/p\u003e\n"]]],["The `ee.Kernel.laplacian4()` function generates a 3x3 Laplacian-4 edge-detection kernel. It accepts `magnitude` (float, default 1) to scale kernel values and `normalize` (boolean, default false) to normalize values to sum to 1. The function returns a kernel represented by the weights matrix: `[[0, 1, 0], [1, -4, 1], [0, 1, 0]]`. `magnitude` allows for customization of the kernel's sensitivity.\n"],null,[]]