import { Image } from '../Image.js'; import type { Mask } from '../Mask.js'; import { subtract } from '../compare/index.js'; import { checkKernel } from '../utils/validators/checkKernel.js'; import checkProcessable from '../utils/validators/checkProcessable.js'; export interface MorphologicalGradientOptions { /** * 3x3 matrix. The kernel can only have ones and zeros. * Accessing a value: kernel[row][column]. * @default `[[1, 1, 1], [1, 1, 1], [1, 1, 1]]` */ kernel?: number[][]; /** * Number of iterations of the algorithm. * @default `1` */ iterations?: number; } export function morphologicalGradient( image: Image, options?: MorphologicalGradientOptions, ): Image; export function morphologicalGradient( image: Mask, options?: MorphologicalGradientOptions, ): Mask; /** * In mathematical morphology and digital image processing, a morphological gradient is the difference between the dilation and the erosion of a given image. It is an image where each pixel value (typically non-negative) indicates the contrast intensity in the close neighborhood of that pixel. It is useful for edge detection and segmentation applications. * @see {@link http://docs.opencv.org/2.4/doc/tutorials/imgproc/opening_closing_hats/opening_closing_hats.html} * @param image - Image to process. * @param options - Morphological gradient hat options. * @returns The processed image. */ export function morphologicalGradient( image: Image | Mask, options: MorphologicalGradientOptions = {}, ) { const { kernel = [ [1, 1, 1], [1, 1, 1], [1, 1, 1], ], iterations = 1, } = options; if (image instanceof Image) { checkProcessable(image, { bitDepth: [1, 8, 16], components: 1, alpha: false, }); } checkKernel(kernel); let newImage = image; for (let i = 0; i < iterations; i++) { const dilatedImage = newImage.dilate({ kernel }); const erodedImage = newImage.erode({ kernel }); newImage = subtract(dilatedImage, erodedImage, { absolute: true }); } return newImage; }