Skip to content
Free public beta until December 4, 2026: every course is open, no card needed. After that, the first chapter of each course stays free and full access is a one-time $39 ($19 for up to 100 founding members chosen for helpful feedback). Your progress is kept. How the beta works

discrete Laplacian

A second-derivative convolution kernel measuring how much a pixel differs from its neighborhood.

The discrete Laplacian, kernel [[0,1,0],[1,-4,1],[0,1,0]], produces a near-zero response in flat regions and a large-magnitude response near edges or fine detail -- a correction signal, not a brightness value, since its entries sum to zero.

See also

unsharp masking
Read the full section →
Graph settings

Calculator