图像处理------Mean Shift滤波(边缘保留的低通滤波) 分类： 视频图像处理 2015-07-24 14:55 45人阅读 评论(0) 收藏

一：Mean Shift算法介绍

Mean Shift是一种聚类算法，在数据挖掘，图像提取，视频对象跟踪中都有应用。本文

重要演示Mean Shift算法来实现图像的低通边缘保留滤波效果。其处理以后的图像有点

类似油画一样。Mean Shift算法的输入参数一般有三个：

1.      矩阵半径r，声明大小

2.      像素距离，常见为欧几里德距离或者曼哈顿距离

3.      像素差值value

 

算法大致的流程如下：

a.      输入像素点P(x, y)

b.      计算该点的像素值pixelv

c.      根据输入的半径r与差值value求出矩阵半径内满足差值像素平均值作为输出像素点值

d.      计算shift与repetition，如果满足条件

e.      继续c ~ d，直到条件不满足退出，得到最终的输出像素值

f.       对输入图像的每个像素重复a ~ e，得到图像输出像素数据

二：色彩空间转换

 本文Mean Shift滤波在YIQ颜色空间上完成，关于RGB与YIQ颜色空间转换可以参考

这里：http://en.wikipedia.org/wiki/YIQ我google找来的转换公式截屏：

三：程序效果

滤镜源代码：

package com.gloomyfish.filter.study;

import java.awt.image.BufferedImage;

public class MeanShiftFilter extends AbstractBufferedImageOp {

    private int radius;
    private float colorDistance;

    public MeanShiftFilter() {
        radius = 3; // default shift radius
        colorDistance = 25; // default color distance
    }
    public int getRadius() {
        return radius;
    }

    public void setRadius(int radius) {
        this.radius = radius;
    }

    public float getColorDistance() {
        return colorDistance;
    }

    public void setColorDistance(float colorDistance) {
        this.colorDistance = colorDistance;
    }

    @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);

        // convert RGB color space to YIQ color space
        float[][] pixelsf = new float[width*height][3];
        for(int i=0; i<inPixels.length; i++) {
            int argb = inPixels[i];
            int r = (argb >> 16) & 0xff;
            int g = (argb >>  8) & 0xff;
            int b = (argb) & 0xff;
            pixelsf[i][0] = 0.299f  *r + 0.587f *g + 0.114f  *b; // Y
            pixelsf[i][1] = 0.5957f *r - 0.2744f*g - 0.3212f *b; // I
            pixelsf[i][2] = 0.2114f *r - 0.5226f*g + 0.3111f *b; // Q
        }

        int index = 0;
        float shift = 0;
        float repetition = 0;
        float radius2 = radius * radius;
        float dis2 = colorDistance * colorDistance;
        for(int row=0; row<height; row++) {
            int ta = 255, tr = 0, tg = 0, tb = 0;
            for(int col=0; col<width; col++) {
                int xc = col;
                int yc = row;
                int xcOld, ycOld;
                float YcOld, IcOld, QcOld;
                index = row*width + col;
                float[] yiq = pixelsf[index];
                float Yc = yiq[0];
                float Ic = yiq[1];
                float Qc = yiq[2];

                repetition = 0;
                do {
                    xcOld = xc;
                    ycOld = yc;
                    YcOld = Yc;
                    IcOld = Ic;
                    QcOld = Qc;

                    float mx = 0;
                    float my = 0;
                    float mY = 0;
                    float mI = 0;
                    float mQ = 0;
                    int num=0;

                    for (int ry=-radius; ry <= radius; ry++) {
                        int y2 = yc + ry;
                        if (y2 >= 0 && y2 < height) {
                            for (int rx=-radius; rx <= radius; rx++) {
                                int x2 = xc + rx;
                                if (x2 >= 0 && x2 < width) {
                                    if (ry*ry + rx*rx <= radius2) {
                                        yiq = pixelsf[y2*width + x2];

                                        float Y2 = yiq[0];
                                        float I2 = yiq[1];
                                        float Q2 = yiq[2];

                                        float dY = Yc - Y2;
                                        float dI = Ic - I2;
                                        float dQ = Qc - Q2;

                                        if (dY*dY+dI*dI+dQ*dQ <= dis2) {
                                            mx += x2;
                                            my += y2;
                                            mY += Y2;
                                            mI += I2;
                                            mQ += Q2;
                                            num++;
                                        }
                                    }
                                }
                            }
                        }
                    }
                    float num_ = 1f/num;
                    Yc = mY*num_;
                    Ic = mI*num_;
                    Qc = mQ*num_;
                    xc = (int) (mx*num_+0.5);
                    yc = (int) (my*num_+0.5);
                    int dx = xc-xcOld;
                    int dy = yc-ycOld;
                    float dY = Yc-YcOld;
                    float dI = Ic-IcOld;
                    float dQ = Qc-QcOld;

                    shift = dx*dx+dy*dy+dY*dY+dI*dI+dQ*dQ;
                    repetition++;
                }
                while (shift > 3 && repetition < 100);
                tr = (int)(Yc + 0.9563f*Ic + 0.6210f*Qc);
                tg = (int)(Yc - 0.2721f*Ic - 0.6473f*Qc);
                tb = (int)(Yc - 1.1070f*Ic + 1.7046f*Qc);
                outPixels[index] = (ta << 24) | (tr << 16) | (tg << 8) | tb;
            }
        }
        setRGB( dest, 0, 0, width, height, outPixels );
        return dest;
    }

    public String toString() {
        System.out.println("Mean Shift Filter...");
        return "MeanShiftFilter";
    }

}

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