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 BottomHatOptions { /** * 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 bottomHat(image: Image, options?: BottomHatOptions): Image; export function bottomHat(image: Mask, options?: BottomHatOptions): Mask; /** * This function is the black top hat (also called bottom hat). * In mathematical morphology and digital image processing, * top-hat transform is an operation that extracts small elements and details from given images. * The black top-hat transform is defined dually as the difference between the closed and the input image. * Top-hat transforms are used for various image processing tasks, such as feature extraction, background equalization, * image enhancement, and others. (Wikipedia) * @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 - Bottom hat options. * @returns The bottom-hatted image. */ export function bottomHat( image: Image | Mask, options: BottomHatOptions = {}, ): Image | Mask { 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 openImage = newImage.close({ kernel }); newImage = subtract(openImage, newImage, { absolute: true }); } return newImage; }