image-js
Version:
Image processing and manipulation in JavaScript
53 lines • 1.82 kB
JavaScript
import { getRadius } from '../utils/getRadius.js';
import { separableConvolution } from './convolution.js';
/**
* Apply a gaussian filter to an image.
* @param image - Image to blur.
* @param options - Gaussian blur options.
* @returns The blurred image.
*/
export function gaussianBlur(image, options) {
if ('sigma' in options) {
const { sigma, size = getSize(sigma), borderType } = options;
const radius = getRadius(size);
const kernel = getKernel(radius, sigma);
return separableConvolution(image, kernel, kernel, {
borderType,
});
}
else if ('sigmaX' in options && 'sigmaY' in options) {
const { sigmaX, sigmaY, sizeX = getSize(sigmaX), sizeY = getSize(sigmaY), borderType, } = options;
const radiusX = getRadius(sizeX);
const radiusY = getRadius(sizeY);
const kernelX = getKernel(radiusX, sigmaX);
const kernelY = getKernel(radiusY, sigmaY);
return separableConvolution(image, kernelX, kernelY, {
borderType,
});
}
else {
throw new TypeError('you must either define sigma or sigmaX and sigmaY in the options argument');
}
}
function getKernel(radius, sigma) {
const n = radius * 2 + 1;
const kernel = new Array(n);
// TODO: check if sigma can really be 0 or undefined.
const sigmaX = sigma || ((n - 1) * 0.5 - 1) * 0.3 + 0.8;
const scale2X = -0.5 / (sigmaX * sigmaX);
let sum = 0;
for (let i = 0; i < n; i++) {
const x = i - radius;
const t = Math.exp(scale2X * x * x);
kernel[i] = t;
sum += t;
}
for (let i = 0; i < n; i++) {
kernel[i] /= sum;
}
return kernel;
}
function getSize(sigma) {
return 2 * Math.ceil(2 * sigma) + 1;
}
//# sourceMappingURL=gaussianBlur.js.map