图像处理之直方图均衡化

来源：互联网发布：dnf优化补丁2017 编辑：程序博客网时间：2024/04/26 11:36

图像处理之直方图均衡化

基本思想：

直方图图均衡化是图像处理中的常用图像增强手段，直方图均衡化的主要优点是

可以降低图像噪声，提升图像的局部显示。对于常见的RGB图像，直方图均衡化

可以分别在三个颜色通道上处理，基本的直方图均衡化的公式为：

其中n_j表示灰度级为R_k的像素的个数，L为图像中灰度总数，对于RGB来说L的

取值范围为[0~255]总灰度级为256个。而R表示输入图像的直方图数据。根据输

出的灰度值S_k计算出输出像素的每个像素值，完成直方图均衡化之后的像素处理

程序效果：

源代码：

package com.gloomyfish.filter.study;import java.awt.image.BufferedImage;public class HistogramEFilter extends AbstractBufferedImageOp{@Overridepublic BufferedImage filter(BufferedImage src, BufferedImage dest) {int width = src.getWidth();        int height = src.getHeight();        if ( dest == null )            dest = createCompatibleDestImage( src, null );        int[] inPixels = new int[width*height];        int[] outPixels = new int[width*height];        getRGB( src, 0, 0, width, height, inPixels );        int[][] rgbhis = new int[3][256]; // RGB        int[][] newrgbhis = new int[3][256]; // after HE        for(int i=0; i<3; i++) {        for(int j=0; j<256; j++) {        rgbhis[i][j] = 0;        newrgbhis[i][j] = 0;        }        }        int index = 0;        int totalPixelNumber = height * width;        for(int row=0; row<height; row++) {        int ta = 0, tr = 0, tg = 0, tb = 0;        for(int col=0; col<width; col++) {        index = row * width + col;        ta = (inPixels[index] >> 24) & 0xff;                tr = (inPixels[index] >> 16) & 0xff;                tg = (inPixels[index] >> 8) & 0xff;                tb = inPixels[index] & 0xff;                // generate original source image RGB histogram                rgbhis[0][tr]++;                rgbhis[1][tg]++;                rgbhis[2][tb]++;        }        }                // generate original source image RGB histogram        generateHEData(newrgbhis, rgbhis, totalPixelNumber, 256);        for(int row=0; row<height; row++) {        int ta = 0, tr = 0, tg = 0, tb = 0;        for(int col=0; col<width; col++) {        index = row * width + col;        ta = (inPixels[index] >> 24) & 0xff;                tr = (inPixels[index] >> 16) & 0xff;                tg = (inPixels[index] >> 8) & 0xff;                tb = inPixels[index] & 0xff;                // get output pixel now...                tr = newrgbhis[0][tr];                tg = newrgbhis[1][tg];                tb = newrgbhis[2][tb];                                outPixels[index] = (ta << 24) | (tr << 16) | (tg << 8) | tb;        }        }        setRGB( dest, 0, 0, width, height, outPixels );        return dest;}/** *  * @param newrgbhis * @param rgbhis * @param totalPixelNumber * @param grayLevel [0 ~ 255] */private void generateHEData(int[][] newrgbhis, int[][] rgbhis, int totalPixelNumber, int grayLevel) {for(int i=0; i<grayLevel; i++) {newrgbhis[0][i] = getNewintensityRate(rgbhis[0], totalPixelNumber, i);newrgbhis[1][i] = getNewintensityRate(rgbhis[1], totalPixelNumber, i);newrgbhis[2][i] = getNewintensityRate(rgbhis[2], totalPixelNumber, i);}}private int getNewintensityRate(int[] grayHis, double totalPixelNumber, int index) {double sum = 0;for(int i=0; i<=index; i++) {sum += ((double)grayHis[i])/totalPixelNumber;}return (int)(sum * 255.0);}}

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