Created
July 3, 2021 02:00
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// Adapted from: https://digitalbunker.dev/2020/09/13/understanding-gaussian-blurs/ | |
function gaussianBlurMatrix(blurRadius: number) { | |
if (blurRadius !== Math.round(blurRadius) || blurRadius <= 0) { | |
throw Error('Blur radius must be a positive integer') | |
} | |
const kernel: number[] = [] | |
const kernelWidth = 1 + 2 * blurRadius | |
const kernelSize = kernelWidth * kernelWidth | |
const sigma = Math.max(1, blurRadius / 2) | |
const exponentDenominator = 2 * sigma * sigma | |
let sum = 0 | |
for (let i = 0; i < kernelSize; i++) { | |
// Distance from center pixel | |
const x = (i % kernelWidth) - blurRadius | |
const y = Math.floor(i / kernelWidth) - blurRadius | |
const exponentNumerator = -(x * x + y * y) | |
const kernelValue = | |
Math.pow(Math.E, exponentNumerator / exponentDenominator) / | |
(Math.PI * exponentDenominator) | |
kernel[i] = kernelValue | |
sum += kernelValue | |
} | |
return kernel.reduce( | |
(matrix, k, i) => | |
matrix + k / sum + (i % kernelWidth == kernelWidth - 1 ? '\n' : ' '), | |
'' | |
) | |
} |
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You can use this with
feConvolveMatrix