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nj表示灰度级为rk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sk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{
@override
public 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);
// 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);
}