图像处理之直方图均衡化

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{  	@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);         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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