1 /* 2 * Copyright 2021 Google LLC 3 * 4 * Licensed under the Apache License, Version 2.0 (the "License"); 5 * you may not use this file except in compliance with the License. 6 * You may obtain a copy of the License at 7 * 8 * http://www.apache.org/licenses/LICENSE-2.0 9 * 10 * Unless required by applicable law or agreed to in writing, software 11 * distributed under the License is distributed on an "AS IS" BASIS, 12 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. 13 * See the License for the specific language governing permissions and 14 * limitations under the License. 15 */ 16 17 package com.google.ux.material.libmonet.quantize; 18 19 import java.util.Map; 20 import java.util.Set; 21 22 /** 23 * An image quantizer that improves on the quality of a standard K-Means algorithm by setting the 24 * K-Means initial state to the output of a Wu quantizer, instead of random centroids. Improves on 25 * speed by several optimizations, as implemented in Wsmeans, or Weighted Square Means, K-Means with 26 * those optimizations. 27 * 28 * <p>This algorithm was designed by M. Emre Celebi, and was found in their 2011 paper, Improving 29 * the Performance of K-Means for Color Quantization. https://arxiv.org/abs/1101.0395 30 */ 31 public final class QuantizerCelebi { QuantizerCelebi()32 private QuantizerCelebi() {} 33 34 /** 35 * Reduce the number of colors needed to represented the input, minimizing the difference between 36 * the original image and the recolored image. 37 * 38 * @param pixels Colors in ARGB format. 39 * @param maxColors The number of colors to divide the image into. A lower number of colors may be 40 * returned. 41 * @return Map with keys of colors in ARGB format, and values of number of pixels in the original 42 * image that correspond to the color in the quantized image. 43 */ quantize(int[] pixels, int maxColors)44 public static Map<Integer, Integer> quantize(int[] pixels, int maxColors) { 45 QuantizerWu wu = new QuantizerWu(); 46 QuantizerResult wuResult = wu.quantize(pixels, maxColors); 47 48 Set<Integer> wuClustersAsObjects = wuResult.colorToCount.keySet(); 49 int index = 0; 50 int[] wuClusters = new int[wuClustersAsObjects.size()]; 51 for (Integer argb : wuClustersAsObjects) { 52 wuClusters[index++] = argb; 53 } 54 55 return QuantizerWsmeans.quantize(pixels, wuClusters, maxColors); 56 } 57 } 58