/**
 * @license
 * Copyright 2021 Google LLC
 *
 * Licensed under the Apache License, Version 2.0 (the "License");
 * you may not use this file except in compliance with the License.
 * You may obtain a copy of the License at
 *
 *      http://www.apache.org/licenses/LICENSE-2.0
 *
 * Unless required by applicable law or agreed to in writing, software
 * distributed under the License is distributed on an "AS IS" BASIS,
 * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
 * See the License for the specific language governing permissions and
 * limitations under the License.
 */
/**
 * An image quantizer that improves on the quality of a standard K-Means
 * algorithm by setting the K-Means initial state to the output of a Wu
 * quantizer, instead of random centroids. Improves on speed by several
 * optimizations, as implemented in Wsmeans, or Weighted Square Means, K-Means
 * with those optimizations.
 *
 * This algorithm was designed by M. Emre Celebi, and was found in their 2011
 * paper, Improving the Performance of K-Means for Color Quantization.
 * https://arxiv.org/abs/1101.0395
 */
export declare class QuantizerCelebi {
    /**
     * @param pixels Colors in ARGB format.
     * @param maxColors The number of colors to divide the image into. A lower
     *     number of colors may be returned.
     * @return Map with keys of colors in ARGB format, and values of number of
     *     pixels in the original image that correspond to the color in the
     *     quantized image.
     */
    static quantize(pixels: number[], maxColors: number): Map<number, number>;
}