0
0

Delete article

Deleted articles cannot be recovered.

Draft of this article would be also deleted.

Are you sure you want to delete this article?

More than 5 years have passed since last update.

Desktop : OpenCV Use EqualizeHist With Add Weight For RGB

Posted at
Goal
OpenCV_ContrastUseEqualizeHistWithAddWeightForRGB.java
import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.imgcodecs.Imgcodecs;
import org.opencv.imgproc.Imgproc;

import javax.swing.*;
import java.awt.*;
import java.awt.image.BufferedImage;
import java.util.ArrayList;
import java.util.List;

public class OpenCV_ContrastUseEqualizeHistWithAddWeightForRGB {

    static {System.loadLibrary(Core.NATIVE_LIBRARY_NAME);}
    private JFrame frmjavaSwing;
    double alpha =2;
    double beta = 2;
    double gamma=1;

    /**
     *  Launch the application.
     */
    public static void main(String[] args){
        EventQueue.invokeLater(new Runnable() {
            @Override
            public void run() {
                try{
                    OpenCV_ContrastUseEqualizeHistWithAddWeightForRGB window = new OpenCV_ContrastUseEqualizeHistWithAddWeightForRGB();
                    window.frmjavaSwing.setVisible(true);
                }catch (Exception e){
                    e.printStackTrace();
                }
            }
        });
    }

    /**
     *  Create the application.
     */
    public OpenCV_ContrastUseEqualizeHistWithAddWeightForRGB(){
        init();
    }

    /**
     *  Init the contents of the frame.
     */
    private void init(){
        final Mat source = Imgcodecs.imread("D:\\projects\\Java\\OpenCV_Samples\\resource\\imgs\\clean.jpg");

        BufferedImage image=matToBufferedImage(equalizeHist(source));

        frmjavaSwing = new JFrame();
        frmjavaSwing.setTitle("opencv彩色影像對比練習1");
        frmjavaSwing.setBounds(100, 100, 520, 550);
        frmjavaSwing.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
        frmjavaSwing.getContentPane().setLayout(null);

        final JLabel lblNewLabel = new JLabel("");
        lblNewLabel.setBounds(10, 10, 438, 455);
        lblNewLabel.setIcon(new ImageIcon(image));
        frmjavaSwing.getContentPane().add(lblNewLabel);
    }

    public Mat equalizeHist(Mat source){
        Mat destination=new Mat(source.rows(),source.cols(),source.type());
        Mat source2=new Mat(source.rows(),source.cols(),source.type());
        List<Mat> bgrList = new ArrayList<>(3);
        Core.split(source,  bgrList);
        Imgproc.equalizeHist(bgrList.get(0), bgrList.get(0));
        Imgproc.equalizeHist(bgrList.get(1), bgrList.get(1));
        Imgproc.equalizeHist(bgrList.get(2), bgrList.get(2));
        Core.merge(bgrList, destination);
        Core.addWeighted(source,alpha,source2,beta,gamma,destination);
        return destination;
    }

    public BufferedImage matToBufferedImage(Mat matrix) {
        int cols = matrix.cols();
        int rows = matrix.rows();
        int elemSize = (int)matrix.elemSize();
        byte[] data = new byte[cols * rows * elemSize];
        int type;
        matrix.get(0, 0, data);
        switch (matrix.channels()) {
            case 1:
                type = BufferedImage.TYPE_BYTE_GRAY;
                break;
            case 3:
                type = BufferedImage.TYPE_3BYTE_BGR;
                // bgr to rgb
                byte b;
                for(int i=0; i<data.length; i=i+3) {
                    b = data[i];
                    data[i] = data[i+2];
                    data[i+2] = b;
                }
                break;
            default:
                return null;
        }
        BufferedImage image2 = new BufferedImage(cols, rows, type);
        image2.getRaster().setDataElements(0, 0, cols, rows, data);
        return image2;
    }
}
Result
![opencv_contrast_use_equalizehist_with_add_weight_for_rgb.JPG](https://qiita-image-store.s3.ap-northeast-1.amazonaws.com/0/276243/66a5e794-0fa4-95cb-b040-914b3c086c69.jpeg)
0
0
0

Register as a new user and use Qiita more conveniently

  1. You get articles that match your needs
  2. You can efficiently read back useful information
  3. You can use dark theme
What you can do with signing up
0
0

Delete article

Deleted articles cannot be recovered.

Draft of this article would be also deleted.

Are you sure you want to delete this article?