OpenCV和Java，Photo类图片修复示例

ASR/CV/ML OpenCV和Java，Photo类图片修复示例

Photo提供了降噪Denosing、动态成像HDR、图片拼接等api，类似于Photoshop。

图片填充：

去色演示：

降噪效果演示：

两张噪点图片：

lena1

lena2

import java.awt.event.ItemEvent;
import java.awt.event.ItemListener;
import java.awt.image.BufferedImage;
import java.util.ArrayList;
import java.util.List;
import javax.swing.ButtonGroup;
import javax.swing.ImageIcon;
import javax.swing.JFrame;
import javax.swing.JLabel;
import javax.swing.JRadioButton;
import javax.swing.JSlider;
import javax.swing.event.ChangeEvent;
import javax.swing.event.ChangeListener;
import org.opencv.core.CvType;
import org.opencv.core.Mat;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.photo.Photo;

public class InPaint extends JFrame {

    private final JLabel imageView;
    private Mat srcMat;

    public InPaint() {
        srcMat = Imgcodecs.imread("./lena_dirty.jpg");

        JLabel inpaintRadiusLabel = new JLabel("半径:" + 0);
        inpaintRadiusLabel.setBounds(15, 10, 60, 15);
        JSlider inpaintRadiusBar = new JSlider(0, 50);
        inpaintRadiusBar.setValue(0);
        inpaintRadiusBar.setBounds(80, 5, 120, 25);
        JRadioButton nsBtn = new JRadioButton("INPAINT_NS");
        nsBtn.setSelected(true);
        nsBtn.setBounds(230, 10, 120, 15);
        JRadioButton teleaBtn = new JRadioButton("INPAINT_TELEA");
        teleaBtn.setBounds(350, 10, 120, 15);
        ButtonGroup group = new ButtonGroup();
        group.add(nsBtn);
        group.add(teleaBtn);

        inpaintRadiusBar.addChangeListener(new ChangeListener() {
            @Override
            public void stateChanged(ChangeEvent e) {
                double value = inpaintRadiusBar.getValue();
                inpaintRadiusLabel.setText("半径:" + value);
                int type = nsBtn.isSelected() ? 1 : 0;
                inpaint(value, type);
            }
        });

        nsBtn.addItemListener(new ItemListener() {
            @Override
            public void itemStateChanged(ItemEvent e) {
                double value = inpaintRadiusBar.getValue();
                inpaintRadiusLabel.setText("半径:" + value);
                int type = nsBtn.isSelected() ? 1 : 0;
                inpaint(value, type);
            }
        });
        teleaBtn.addItemListener(new ItemListener() {
            @Override
            public void itemStateChanged(ItemEvent e) {
                double value = inpaintRadiusBar.getValue();
                inpaintRadiusLabel.setText("半径:" + value);
                int type = nsBtn.isSelected() ? 1 : 0;
                inpaint(value, type);
            }
        });

        imageView = new JLabel();
        imageView.setBounds(5, 5, 512, 512);
        this.setTitle("图片处理");
        this.setSize(550, 580);
        this.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
        this.getContentPane().setLayout(null);
        this.getContentPane().add(inpaintRadiusLabel);
        this.getContentPane().add(inpaintRadiusBar);
        this.getContentPane().add(nsBtn);
        this.getContentPane().add(teleaBtn);
        this.getContentPane().add(imageView);

        setIcon(srcMat);
    }

    /**
     * 区域填充
     *
     * @param inpaintRadius 数值越大，修复区域越模糊-过渡越好
     * @param flags         本例 INPAINT_TELEA 慢于 INPAINT_NS
     */
    private void inpaint(double inpaintRadius, int flags) {
        Mat dstMat = new Mat(srcMat.size(), CvType.CV_8UC3);
        Mat inpaintMaskMat = Imgcodecs.imread("./lena_dirtymask.jpg", CvType.CV_8UC1); // 模拟手动选择的要修复的区域
        if (1 == flags) {
            Photo.inpaint(srcMat, inpaintMaskMat, dstMat, inpaintRadius, Photo.INPAINT_NS);    // 边缘线算法
        } else {
            Photo.inpaint(srcMat, inpaintMaskMat, dstMat, inpaintRadius, Photo.INPAINT_TELEA); // 临近像素算法
        }
        setIcon(dstMat);
    }
    
    // 去色
    private void decolor() {
        srcMat = Imgcodecs.imread("./lena.jpg");
        Mat grayscaleMat = new Mat();  // 灰阶图，8位单通道
        Mat colorBoostMat = new Mat(); // 彩图，8位三通道
        Photo.decolor(srcMat, grayscaleMat, colorBoostMat);

        setIcon(grayscaleMat);
        setIcon(colorBoostMat);
    }

    // 降噪-去除杂点。图片整体上有种柔化的感觉
    private void fastNlMeansDenoising(){
        Mat dstMat = new Mat();
        
        // 方法1。可用于单通道、3通道图
        // fastNlMeansDenoising(Mat src, Mat& dst, float h = 3, int templateWindowSize = 7, int searchWindowSize = 21)
        Photo.fastNlMeansDenoising(srcMat, dstMat);
        
        // 方法2。按照索引去除杂点。可用于单通道、3通道图
        Mat im1 = Imgcodecs.imread("./lena1.jpg",Imgcodecs.CV_LOAD_IMAGE_COLOR);
        Mat im2 = Imgcodecs.imread("./lena2.jpg",Imgcodecs.CV_LOAD_IMAGE_COLOR);
        List<Mat> srcImgs=new ArrayList<>();
        srcImgs.add(im1); // 杂点图片
        srcImgs.add(im2); // 杂点图片
        srcImgs.add(srcMat);
        // fastNlMeansDenoisingMulti(vector_Mat srcImgs, Mat& dst, int imgToDenoiseIndex, int temporalWindowSize, float h = 3, int templateWindowSize = 7, int searchWindowSize = 21)
        // imgToDenoiseIndex 指srcImgs中"杂点的索引"图片的索引。
        // temporalWindowSize 要去除的杂点周围的像素数量，须奇数。
        Photo.fastNlMeansDenoisingMulti(srcImgs, dstMat, 2, 1);

        // 方法3。可用于3通道图
        // fastNlMeansDenoisingColored(Mat src, Mat& dst, float h = 3, float hColor = 3, int templateWindowSize = 7, int searchWindowSize = 21)
        Photo.fastNlMeansDenoisingColored(srcMat, dstMat);

        // 方法4
        // fastNlMeansDenoisingColoredMulti(vector_Mat srcImgs, Mat& dst, int imgToDenoiseIndex, int temporalWindowSize, float h = 3, float hColor = 3, int templateWindowSize = 7, int searchWindowSize = 21)
        Photo.fastNlMeansDenoisingColoredMulti(srcImgs, dstMat, 2, 1); 

        // 方法5 
        Mat img = Imgcodecs.imread("./lena.jpg",Imgcodecs.CV_LOAD_IMAGE_GRAYSCALE); // 转灰度图 CV_LOAD_IMAGE_GRAYSCALE ：gray = 0.299 * r + 0.587 * g + 0.114 * b ，小数点部分四舍五入为整数
        Mat img1 = Imgcodecs.imread("./lena1.jpg",Imgcodecs.CV_LOAD_IMAGE_GRAYSCALE);
        Mat img2 = Imgcodecs.imread("./lena2.jpg",Imgcodecs.CV_LOAD_IMAGE_GRAYSCALE);
        List<Mat> srcList=new ArrayList<Mat>();
        srcList.add(img);
        // srcList.add(img1);
        // srcList.add(img2); 
        // denoise_TVL1(vector_Mat observations, Mat result, double lambda = 1.0, int niters = 30)
        // lambda 数值越小，图像越模糊-柔化
        // niters 运算次数
        Photo.denoise_TVL1(srcList, dstMat, 10, 10);
        
        setIcon(dstMat);
    }

    private void setIcon(Mat mat) {
        BufferedImage image = CVUtil.matToBufferedImage(mat); // CVUtil 见 http://www.gaohaiyan.com/3229.html
        imageView.setIcon(new ImageIcon(image));
    }
}

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import java.awt.event.ItemEvent;

import java.awt.event.ItemListener;

import java.awt.image.BufferedImage;

import java.util.ArrayList;

import java.util.List;

import javax.swing.ButtonGroup;

import javax.swing.ImageIcon;

import javax.swing.JFrame;

import javax.swing.JLabel;

import javax.swing.JRadioButton;

import javax.swing.JSlider;

import javax.swing.event.ChangeEvent;

import javax.swing.event.ChangeListener;

import org.opencv.core.CvType;

import org.opencv.core.Mat;

import org.opencv.imgcodecs.Imgcodecs;

import org.opencv.photo.Photo;

public class InPaint extends JFrame {

private final JLabel imageView;

private Mat srcMat;

public InPaint() {

srcMat = Imgcodecs.imread("./lena_dirty.jpg");

JLabel inpaintRadiusLabel = new JLabel("半径:" + 0);

inpaintRadiusLabel.setBounds(15, 10, 60, 15);

JSlider inpaintRadiusBar = new JSlider(0, 50);

inpaintRadiusBar.setValue(0);

inpaintRadiusBar.setBounds(80, 5, 120, 25);

JRadioButton nsBtn = new JRadioButton("INPAINT_NS");

nsBtn.setSelected(true);

nsBtn.setBounds(230, 10, 120, 15);

JRadioButton teleaBtn = new JRadioButton("INPAINT_TELEA");

teleaBtn.setBounds(350, 10, 120, 15);

ButtonGroup group = new ButtonGroup();

group.add(nsBtn);

group.add(teleaBtn);

inpaintRadiusBar.addChangeListener(new ChangeListener() {

@Override

public void stateChanged(ChangeEvent e) {

double value = inpaintRadiusBar.getValue();

inpaintRadiusLabel.setText("半径:" + value);

int type = nsBtn.isSelected() ? 1 : 0;

inpaint(value, type);

}

});

nsBtn.addItemListener(new ItemListener() {

@Override

public void itemStateChanged(ItemEvent e) {

double value = inpaintRadiusBar.getValue();

inpaintRadiusLabel.setText("半径:" + value);

int type = nsBtn.isSelected() ? 1 : 0;

inpaint(value, type);

}

});

teleaBtn.addItemListener(new ItemListener() {

@Override

public void itemStateChanged(ItemEvent e) {

double value = inpaintRadiusBar.getValue();

inpaintRadiusLabel.setText("半径:" + value);

int type = nsBtn.isSelected() ? 1 : 0;

inpaint(value, type);

}

});

imageView = new JLabel();

imageView.setBounds(5, 5, 512, 512);

this.setTitle("图片处理");

this.setSize(550, 580);

this.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);

this.getContentPane().setLayout(null);

this.getContentPane().add(inpaintRadiusLabel);

this.getContentPane().add(inpaintRadiusBar);

this.getContentPane().add(nsBtn);

this.getContentPane().add(teleaBtn);

this.getContentPane().add(imageView);

setIcon(srcMat);

}

/**

* 区域填充

* @param inpaintRadius 数值越大，修复区域越模糊-过渡越好

* @param flags 本例 INPAINT_TELEA 慢于 INPAINT_NS

private void inpaint(double inpaintRadius, int flags) {

Mat dstMat = new Mat(srcMat.size(), CvType.CV_8UC3);

Mat inpaintMaskMat = Imgcodecs.imread("./lena_dirtymask.jpg", CvType.CV_8UC1); // 模拟手动选择的要修复的区域

if (1 == flags) {

Photo.inpaint(srcMat, inpaintMaskMat, dstMat, inpaintRadius, Photo.INPAINT_NS); // 边缘线算法

} else {

Photo.inpaint(srcMat, inpaintMaskMat, dstMat, inpaintRadius, Photo.INPAINT_TELEA); // 临近像素算法

}

setIcon(dstMat);

}

// 去色

private void decolor() {

srcMat = Imgcodecs.imread("./lena.jpg");

Mat grayscaleMat = new Mat(); // 灰阶图，8位单通道

Mat colorBoostMat = new Mat(); // 彩图，8位三通道

Photo.decolor(srcMat, grayscaleMat, colorBoostMat);

setIcon(grayscaleMat);

setIcon(colorBoostMat);

}

// 降噪-去除杂点。图片整体上有种柔化的感觉

private void fastNlMeansDenoising(){

Mat dstMat = new Mat();

// 方法1。可用于单通道、3通道图

// fastNlMeansDenoising(Mat src, Mat& dst, float h = 3, int templateWindowSize = 7, int searchWindowSize = 21)

Photo.fastNlMeansDenoising(srcMat, dstMat);

// 方法2。按照索引去除杂点。可用于单通道、3通道图

Mat im1 = Imgcodecs.imread("./lena1.jpg",Imgcodecs.CV_LOAD_IMAGE_COLOR);

Mat im2 = Imgcodecs.imread("./lena2.jpg",Imgcodecs.CV_LOAD_IMAGE_COLOR);

List<Mat> srcImgs=new ArrayList<>();

srcImgs.add(im1); // 杂点图片

srcImgs.add(im2); // 杂点图片

srcImgs.add(srcMat);

// fastNlMeansDenoisingMulti(vector_Mat srcImgs, Mat& dst, int imgToDenoiseIndex, int temporalWindowSize, float h = 3, int templateWindowSize = 7, int searchWindowSize = 21)

// imgToDenoiseIndex 指srcImgs中"杂点的索引"图片的索引。

// temporalWindowSize 要去除的杂点周围的像素数量，须奇数。

Photo.fastNlMeansDenoisingMulti(srcImgs, dstMat, 2, 1);

// 方法3。可用于3通道图

// fastNlMeansDenoisingColored(Mat src, Mat& dst, float h = 3, float hColor = 3, int templateWindowSize = 7, int searchWindowSize = 21)

Photo.fastNlMeansDenoisingColored(srcMat, dstMat);

// 方法4

// fastNlMeansDenoisingColoredMulti(vector_Mat srcImgs, Mat& dst, int imgToDenoiseIndex, int temporalWindowSize, float h = 3, float hColor = 3, int templateWindowSize = 7, int searchWindowSize = 21)

Photo.fastNlMeansDenoisingColoredMulti(srcImgs, dstMat, 2, 1);

// 方法5

Mat img = Imgcodecs.imread("./lena.jpg",Imgcodecs.CV_LOAD_IMAGE_GRAYSCALE); // 转灰度图 CV_LOAD_IMAGE_GRAYSCALE ：gray = 0.299 * r + 0.587 * g + 0.114 * b ，小数点部分四舍五入为整数

Mat img1 = Imgcodecs.imread("./lena1.jpg",Imgcodecs.CV_LOAD_IMAGE_GRAYSCALE);

Mat img2 = Imgcodecs.imread("./lena2.jpg",Imgcodecs.CV_LOAD_IMAGE_GRAYSCALE);

List<Mat> srcList=new ArrayList<Mat>();

srcList.add(img);

// srcList.add(img1);

// srcList.add(img2);

// denoise_TVL1(vector_Mat observations, Mat result, double lambda = 1.0, int niters = 30)

// lambda 数值越小，图像越模糊-柔化

// niters 运算次数

Photo.denoise_TVL1(srcList, dstMat, 10, 10);

setIcon(dstMat);

}

private void setIcon(Mat mat) {

BufferedImage image = CVUtil.matToBufferedImage(mat); // CVUtil 见 http://www.gaohaiyan.com/3229.html

imageView.setIcon(new ImageIcon(image));

}

- end

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