图像处理------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：

[java] view plaincopypackage 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]++;
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];
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);
}

}