Java实现Canny算子边缘提取

程序员文章站 2022-07-14 11:57:06
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如下代码：
import java.util.Arrays;

import javafx.scene.image.PixelReader;
import javafx.scene.image.PixelWriter;
import javafx.scene.image.WritableImage;

public class Canny {
    private float gaussianKernelRadius = 2f;  
    private int gaussianKernelWidth = 16;  
    private float lowThreshold = 2.5f;  
    private float highThreshold = 7.5f;  
    // image width, height  
    private int width;  
    private int height;  
    private float[] data;  
    private float[] magnitudes;

    //传入被处理图片，返回边缘提取效果图
    public WritableImage filter(WritableImage src) {  
        width = (int) src.getWidth();  
        height = (int) src.getHeight(); 

        WritableImage outImage = new WritableImage(width,height);

        // 图像灰度化  
        int[] inPixels = new int[width * height];  
        int[] outPixels = new int[width * height];  
        getRGB(src, 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);  
                inPixels[index] = (ta << 24) | (gray << 16) | (gray << 8)  
                        | gray;  
            }  
        }  

        // 计算高斯卷积核  
        float kernel[][] = new float[gaussianKernelWidth][gaussianKernelWidth];  
        for(int x=0; x<gaussianKernelWidth; x++)  
        {  
            for(int y=0; y<gaussianKernelWidth; y++)  
            {  
                kernel[x][y] = gaussian(x, y, gaussianKernelRadius);  
            }  
        }  
        // 高斯模糊 -灰度图像  
        int krr = (int)gaussianKernelRadius;  
        for (int row = 0; row < height; row++) {  
            for (int col = 0; col < width; col++) {  
                index = row * width + col;  
                double weightSum = 0.0;  
                double redSum = 0;  
                for(int subRow=-krr; subRow<=krr; subRow++)  
                {  
                    int nrow = row + subRow;  
                    if(nrow >= height || nrow < 0)  
                    {  
                        nrow = 0;  
                    }  
                    for(int subCol=-krr; subCol<=krr; subCol++)  
                    {  
                        int ncol = col + subCol;  
                        if(ncol >= width || ncol <=0)  
                        {  
                            ncol = 0;  
                        }  
                        int index2 = nrow * width + ncol;  
                        int tr1 = (inPixels[index2] >> 16) & 0xff;  
                        redSum += tr1*kernel[subRow+krr][subCol+krr];  
                        weightSum += kernel[subRow+krr][subCol+krr];  
                    }  
                }  
                int gray = (int)(redSum / weightSum);  
                outPixels[index] = gray;  
            }  
        }  

        // 计算梯度-gradient, X放与Y方向  
        data = new float[width * height];  
        magnitudes = new float[width * height];  
        for (int row = 0; row < height; row++) {  
            for (int col = 0; col < width; col++) {  
                index = row * width + col;  
                // 计算X方向梯度  
                float xg = (getPixel(outPixels, width, height, col, row+1) -   
                        getPixel(outPixels, width, height, col, row) +   
                        getPixel(outPixels, width, height, col+1, row+1) -  
                        getPixel(outPixels, width, height, col+1, row))/2.0f;  
                float yg = (getPixel(outPixels, width, height, col, row)-  
                        getPixel(outPixels, width, height, col+1, row) +  
                        getPixel(outPixels, width, height, col, row+1) -  
                        getPixel(outPixels, width, height, col+1, row+1))/2.0f;  
                // 计算振幅与角度  
                data[index] = hypot(xg, yg);  
                if(xg == 0)  
                {  
                    if(yg > 0)  
                    {  
                        magnitudes[index]=90;                         
                    }  
                    if(yg < 0)  
                    {  
                        magnitudes[index]=-90;  
                    }  
                }  
                else if(yg == 0)  
                {  
                    magnitudes[index]=0;  
                }  
                else  
                {  
                    magnitudes[index] = (float)((Math.atan(yg/xg) * 180)/Math.PI);                    
                }  
                // make it 0 ~ 180  
                magnitudes[index] += 90;  
            }  
        }  

        // 非最大信号压制算法 3x3  
        Arrays.fill(magnitudes, 0);  

        for (int row = 0; row < height; row++) {  
            for (int col = 0; col < width; col++) {  
                index = row * width + col;  
                float angle = magnitudes[index];  
                float m0 = data[index];  
                magnitudes[index] = m0;  
                if(angle >=0 && angle < 22.5) // angle 0  
                {  
                    float m1 = getPixel(data, width, height, col-1, row);  
                    float m2 = getPixel(data, width, height, col+1, row);  
                    if(m0 < m1 || m0 < m2)  
                    {  
                        magnitudes[index] = 0;  
                    }  
                }  
                else if(angle >= 22.5 && angle < 67.5) // angle +45  
                {  
                    float m1 = getPixel(data, width, height, col+1, row-1);  
                    float m2 = getPixel(data, width, height, col-1, row+1);  
                    if(m0 < m1 || m0 < m2)  
                    {  
                        magnitudes[index] = 0;  
                    }  
                }  
                else if(angle >= 67.5 && angle < 112.5) // angle 90  
                {  
                    float m1 = getPixel(data, width, height, col, row+1);  
                    float m2 = getPixel(data, width, height, col, row-1);  
                    if(m0 < m1 || m0 < m2)  
                    {  
                        magnitudes[index] = 0;  
                    }  
                }  
                else if(angle >=112.5 && angle < 157.5) // angle 135 / -45  
                {  
                    float m1 = getPixel(data, width, height, col-1, row-1);  
                    float m2 = getPixel(data, width, height, col+1, row+1);  
                    if(m0 < m1 || m0 < m2)  
                    {  
                        magnitudes[index] = 0;  
                    }  
                }  
                else if(angle >=157.5) // angle 0  
                {  
                    float m1 = getPixel(data, width, height, col, row+1);  
                    float m2 = getPixel(data, width, height, col, row-1);  
                    if(m0 < m1 || m0 < m2)  
                    {  
                        magnitudes[index] = 0;  
                    }  
                }  
            }  
        }  
        // 寻找最大与最小值  
        float min = 255;  
        float max = 0;  
        for(int i=0; i<magnitudes.length; i++)  
        {  
            if(magnitudes[i] == 0) continue;  
            min = Math.min(min, magnitudes[i]);  
            max = Math.max(max, magnitudes[i]);  
        }  
        System.out.println("Image Max Gradient = " + max + " Mix Gradient = " + min);  

        // 通常比值为 TL : TH = 1 : 3， 根据两个阈值完成二值化边缘连接  
        // 边缘连接-link edges  
        Arrays.fill(data, 0); 

        int offset = 0;  
        for (int row = 0; row < height; row++) {  
            for (int col = 0; col < width; col++) {  
                if(magnitudes[offset] >= highThreshold && data[offset] == 0)  
                {  
                    edgeLink(col, row, offset, lowThreshold);  
                }  
                offset++;  
            }  
        }  

        // 二值化显示  
        for(int i=0; i<inPixels.length; i++)  
        {  
            int gray = clamp((int)data[i]);  
            outPixels[i] = gray > 0 ? -1 : 0xff000000;       
        }  

        PixelWriter pixel = outImage.getPixelWriter();

        for(int i=0;i<height;i++) {
            for(int j=0;j<width;j++) {
                pixel.setArgb(j, i, outPixels[i*width+j]);
            }
        }
        return outImage;  
    }  

    public int clamp(int value) {  
        return value > 255 ? 255 :  
            (value < 0 ? 0 : value);  
    }  

    private void edgeLink(int x1, int y1, int index, float threshold) {  
        int x0 = (x1 == 0) ? x1 : x1 - 1;  
        int x2 = (x1 == width - 1) ? x1 : x1 + 1;  
        int y0 = y1 == 0 ? y1 : y1 - 1;  
        int y2 = y1 == height -1 ? y1 : y1 + 1;  

        data[index] = magnitudes[index];  
        for (int x = x0; x <= x2; x++) {  
            for (int y = y0; y <= y2; y++) {  
                int i2 = x + y * width;  
                if ((y != y1 || x != x1)  
                    && data[i2] == 0   
                    && magnitudes[i2] >= threshold) {  
                    edgeLink(x, y, i2, threshold);  
                    return;  
                }  
            }  
        }  
    }  

    private float getPixel(float[] input, int width, int height, int col,  
            int row) {  
        if(col < 0 || col >= width)  
            col = 0;  
        if(row < 0 || row >= height)  
            row = 0;  
        int index = row * width + col;  
        return input[index];  
    }  

    private float hypot(float x, float y) {  
        return (float) Math.hypot(x, y);  
    }  

    private int getPixel(int[] inPixels, int width, int height, int col,  
            int row) {  
        if(col < 0 || col >= width)  
            col = 0;  
        if(row < 0 || row >= height)  
            row = 0;  
        int index = row * width + col;  
        return inPixels[index];  
    }  

    private float gaussian(float x, float y, float sigma) {  
        float xDistance = x*x;  
        float yDistance = y*y;  
        float sigma22 = 2*sigma*sigma;  
        float sigma22PI = (float)Math.PI * sigma22;  
        return (float)Math.exp(-(xDistance + yDistance)/sigma22)/sigma22PI;  
    }  

    private void getRGB(WritableImage image, int width, int height, int[] inPixel) {
        PixelReader reader = image.getPixelReader();
        for(int i=0;i<height;i++) {
            for(int j=0;j<width;j++) {
                inPixel[i*width+j] = reader.getArgb(j, i);
            }
        }
    }
}