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Filename : array.ts
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/**
 * @preserve
 * Copyright 2015-2018 Igor Bezkrovnyi
 * All rights reserved. (MIT Licensed)
 *
 * ditherErrorDiffusionArray.ts - part of Image Quantization Library
 */
import { AbstractImageQuantizer } from './imageQuantizer';
import { AbstractDistanceCalculator } from '../distance/distanceCalculator';
import { PointContainer } from '../utils/pointContainer';
import { Palette } from '../utils/palette';
import { Point } from '../utils/point';
import { inRange0to255Rounded } from '../utils/arithmetic';
import { ImageQuantizerYieldValue } from './imageQuantizerYieldValue';
import { ProgressTracker } from '../utils/progressTracker';

// TODO: is it the best name for this enum "kernel"?
export enum ErrorDiffusionArrayKernel {
  FloydSteinberg = 0,
  FalseFloydSteinberg,
  Stucki,
  Atkinson,
  Jarvis,
  Burkes,
  Sierra,
  TwoSierra,
  SierraLite,
}

// http://www.tannerhelland.com/4660/dithering-eleven-algorithms-source-code/
export class ErrorDiffusionArray extends AbstractImageQuantizer {
  private _minColorDistance: number;
  private _serpentine: boolean;
  private _kernel!: number[][];
  /** true = GIMP, false = XNVIEW */
  private _calculateErrorLikeGIMP: boolean;

  private _distance: AbstractDistanceCalculator;

  constructor(
    colorDistanceCalculator: AbstractDistanceCalculator,
    kernel: ErrorDiffusionArrayKernel,
    serpentine = true,
    minimumColorDistanceToDither = 0,
    calculateErrorLikeGIMP = false,
  ) {
    super();
    this._setKernel(kernel);

    this._distance = colorDistanceCalculator;
    this._minColorDistance = minimumColorDistanceToDither;
    this._serpentine = serpentine;
    this._calculateErrorLikeGIMP = calculateErrorLikeGIMP;
  }

  /**
   * adapted from http://jsbin.com/iXofIji/2/edit by PAEz
   * fixed version. it doesn't use image pixels as error storage, also it doesn't have 0.3 + 0.3 + 0.3 + 0.3 = 0 error
   * Mutates pointContainer
   */
  *quantize(
    pointContainer: PointContainer,
    palette: Palette,
  ): IterableIterator<ImageQuantizerYieldValue> {
    const pointArray = pointContainer.getPointArray();
    const originalPoint = new Point();
    const width = pointContainer.getWidth();
    const height = pointContainer.getHeight();
    const errorLines: number[][][] = [];

    let dir = 1;
    let maxErrorLines = 1;

    // initial error lines (number is taken from dithering kernel)
    for (const kernel of this._kernel) {
      const kernelErrorLines = kernel[2] + 1;
      if (maxErrorLines < kernelErrorLines) maxErrorLines = kernelErrorLines;
    }
    for (let i = 0; i < maxErrorLines; i++) {
      this._fillErrorLine((errorLines[i] = []), width);
    }

    const tracker = new ProgressTracker(height, 99);
    for (let y = 0; y < height; y++) {
      if (tracker.shouldNotify(y)) {
        yield {
          progress: tracker.progress,
        };
      }

      // always serpentine
      if (this._serpentine) dir *= -1;

      const lni = y * width;
      const xStart = dir === 1 ? 0 : width - 1;
      const xEnd = dir === 1 ? width : -1;

      // cyclic shift with erasing
      this._fillErrorLine(errorLines[0], width);
      // TODO: why it is needed to cast types here?
      errorLines.push(errorLines.shift() as number[][]);

      const errorLine = errorLines[0];
      for (
        let x = xStart, idx = lni + xStart;
        x !== xEnd;
        x += dir, idx += dir
      ) {
        // Image pixel
        const point = pointArray[idx];
        // originalPoint = new Utils.Point(),
        const error = errorLine[x];

        originalPoint.from(point);

        const correctedPoint = Point.createByRGBA(
          inRange0to255Rounded(point.r + error[0]),
          inRange0to255Rounded(point.g + error[1]),
          inRange0to255Rounded(point.b + error[2]),
          inRange0to255Rounded(point.a + error[3]),
        );

        // Reduced pixel
        const palettePoint = palette.getNearestColor(
          this._distance,
          correctedPoint,
        );
        point.from(palettePoint);

        // dithering strength
        if (this._minColorDistance) {
          const dist = this._distance.calculateNormalized(
            originalPoint,
            palettePoint,
          );
          if (dist < this._minColorDistance) continue;
        }

        // Component distance
        let er;
        let eg;
        let eb;
        let ea;
        if (this._calculateErrorLikeGIMP) {
          er = correctedPoint.r - palettePoint.r;
          eg = correctedPoint.g - palettePoint.g;
          eb = correctedPoint.b - palettePoint.b;
          ea = correctedPoint.a - palettePoint.a;
        } else {
          er = originalPoint.r - palettePoint.r;
          eg = originalPoint.g - palettePoint.g;
          eb = originalPoint.b - palettePoint.b;
          ea = originalPoint.a - palettePoint.a;
        }

        const dStart = dir === 1 ? 0 : this._kernel.length - 1;
        const dEnd = dir === 1 ? this._kernel.length : -1;

        for (let i = dStart; i !== dEnd; i += dir) {
          const x1 = this._kernel[i][1] * dir;
          const y1 = this._kernel[i][2];

          if (x1 + x >= 0 && x1 + x < width && y1 + y >= 0 && y1 + y < height) {
            const d = this._kernel[i][0];
            const e = errorLines[y1][x1 + x];

            e[0] += er * d;
            e[1] += eg * d;
            e[2] += eb * d;
            e[3] += ea * d;
          }
        }
      }
    }

    yield {
      pointContainer,
      progress: 100,
    };
  }

  private _fillErrorLine(errorLine: number[][], width: number) {
    // shrink
    if (errorLine.length > width) {
      errorLine.length = width;
    }

    // reuse existing arrays
    const l = errorLine.length;
    for (let i = 0; i < l; i++) {
      const error = errorLine[i];
      error[0] = error[1] = error[2] = error[3] = 0;
    }

    // create missing arrays
    for (let i = l; i < width; i++) {
      errorLine[i] = [0.0, 0.0, 0.0, 0.0];
    }
  }

  private _setKernel(kernel: ErrorDiffusionArrayKernel) {
    switch (kernel) {
      case ErrorDiffusionArrayKernel.FloydSteinberg:
        this._kernel = [
          [7 / 16, 1, 0],
          [3 / 16, -1, 1],
          [5 / 16, 0, 1],
          [1 / 16, 1, 1],
        ];
        break;

      case ErrorDiffusionArrayKernel.FalseFloydSteinberg:
        this._kernel = [
          [3 / 8, 1, 0],
          [3 / 8, 0, 1],
          [2 / 8, 1, 1],
        ];
        break;

      case ErrorDiffusionArrayKernel.Stucki:
        this._kernel = [
          [8 / 42, 1, 0],
          [4 / 42, 2, 0],
          [2 / 42, -2, 1],
          [4 / 42, -1, 1],
          [8 / 42, 0, 1],
          [4 / 42, 1, 1],
          [2 / 42, 2, 1],
          [1 / 42, -2, 2],
          [2 / 42, -1, 2],
          [4 / 42, 0, 2],
          [2 / 42, 1, 2],
          [1 / 42, 2, 2],
        ];
        break;

      case ErrorDiffusionArrayKernel.Atkinson:
        this._kernel = [
          [1 / 8, 1, 0],
          [1 / 8, 2, 0],
          [1 / 8, -1, 1],
          [1 / 8, 0, 1],
          [1 / 8, 1, 1],
          [1 / 8, 0, 2],
        ];
        break;

      case ErrorDiffusionArrayKernel.Jarvis:
        this._kernel = [
          // Jarvis, Judice, and Ninke / JJN?
          [7 / 48, 1, 0],
          [5 / 48, 2, 0],
          [3 / 48, -2, 1],
          [5 / 48, -1, 1],
          [7 / 48, 0, 1],
          [5 / 48, 1, 1],
          [3 / 48, 2, 1],
          [1 / 48, -2, 2],
          [3 / 48, -1, 2],
          [5 / 48, 0, 2],
          [3 / 48, 1, 2],
          [1 / 48, 2, 2],
        ];
        break;

      case ErrorDiffusionArrayKernel.Burkes:
        this._kernel = [
          [8 / 32, 1, 0],
          [4 / 32, 2, 0],
          [2 / 32, -2, 1],
          [4 / 32, -1, 1],
          [8 / 32, 0, 1],
          [4 / 32, 1, 1],
          [2 / 32, 2, 1],
        ];
        break;

      case ErrorDiffusionArrayKernel.Sierra:
        this._kernel = [
          [5 / 32, 1, 0],
          [3 / 32, 2, 0],
          [2 / 32, -2, 1],
          [4 / 32, -1, 1],
          [5 / 32, 0, 1],
          [4 / 32, 1, 1],
          [2 / 32, 2, 1],
          [2 / 32, -1, 2],
          [3 / 32, 0, 2],
          [2 / 32, 1, 2],
        ];
        break;

      case ErrorDiffusionArrayKernel.TwoSierra:
        this._kernel = [
          [4 / 16, 1, 0],
          [3 / 16, 2, 0],
          [1 / 16, -2, 1],
          [2 / 16, -1, 1],
          [3 / 16, 0, 1],
          [2 / 16, 1, 1],
          [1 / 16, 2, 1],
        ];
        break;

      case ErrorDiffusionArrayKernel.SierraLite:
        this._kernel = [
          [2 / 4, 1, 0],
          [1 / 4, -1, 1],
          [1 / 4, 0, 1],
        ];
        break;

      default:
        throw new Error(`ErrorDiffusionArray: unknown kernel = ${kernel}`);
    }
  }
}