图像处理之积分图应用四（基于局部均值的图像二值化算法）
基本原理
均值法，选择的阈值是局部范围内像素的灰度均值(gray mean)，该方法的一个变种是用常量C减去均值Mean，然后根据均值实现如下操作：
pixel = (pixel > (mean - c)) ? object : background
其中默认情况下参数C取值为0。object表示前景像素，background表示背景像素。
实现步骤
1. 彩色图像转灰度图像
2. 获取灰度图像的像素数据，预计算积分图
3. 根据输入的参数窗口半径大小从积分图中获取像素总和，求得平均值
4.循环每个像素，根据局部均值实现中心像素的二值化赋值
5.输入二值图像
运行结果：
代码实现：
package com.gloomyfish.ii.demo;
import java.awt.image.BufferedImage;
public class FastMeanBinaryFilter extends AbstractImageOptionFilter {
private int constant;
private int radius;
public FastMeanBinaryFilter() {
constant = 10;
radius = 7; // 1,2,3,4,5,6,7,8
}
public int getConstant() {
return constant;
}
public void setConstant(int constant) {
this.constant = constant;
}
public int getRadius() {
return radius;
}
public void setRadius(int radius) {
this.radius = radius;
}
@Override
public BufferedImage process(BufferedImage image) {
int width = image.getWidth();
int height = image.getHeight();
BufferedImage dest = createCompatibleDestImage( image, null );
// 图像灰度化
int[] inPixels = new int[width*height];
int[] outPixels = new int[width*height];
byte[] binData = new byte[width*height];
getRGB( image, 0, 0, width, height, inPixels );
int index = 0;
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;
int gray= (int)(0.299 *tr + 0.587*tg + 0.114*tb);
binData[index] = (byte)gray;
}
}
// per-calculate integral image
IntIntegralImage grayii = new IntIntegralImage();
grayii.setImage(binData);
grayii.process(width, height);
int yr = radius;
int xr = radius;
int size = (yr * 2 + 1)*(xr * 2 + 1);
for (int row = 0; row < height; row++) {
for (int col = 0; col < width; col++) {
index = row * width + col;
// 计算均值
int sr = grayii.getBlockSum(col, row, (yr * 2 + 1), (xr * 2 + 1));
int mean = sr / size;
int pixel = binData[index]&0xff;
// 二值化
if(pixel > (mean-constant)) {
outPixels[row * width + col] = (0xff << 24) | (0xff << 16) | (0xff << 8) | 0xff;
} else {
outPixels[row * width + col] = (0xff << 24) | (0x00 << 16) | (0x00 << 8) | 0x00;
}
}
}
// 返回结果
setRGB(dest, 0, 0, width, height, outPixels);
return dest;
}
}
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