使用OpenCV给给定的图像添加噪声-
将给定图像的内容读取到mat对象中。
创建两个空矩阵，用于存储噪声和结果
创建两个MatOfDouble矩阵来存储均值和标准差。
使用meanStdDev()函数获取均值和标准差的值 使用randn()方法创建一个带有随机元素的矩阵（用于存储噪声）。
将上述创建的源、均值和标准差传递给这个方法 objects.
最后，将噪声矩阵和源矩阵相加，并保存为目标矩阵。
示例
import java.awt.Image;
import java.awt.image.BufferedImage;
import java.io.IOException;
import javafx.application.Application;
import javafx.embed.swing.SwingFXUtils;
import javafx.scene.Group;
import javafx.scene.Scene;
import javafx.scene.image.ImageView;
import javafx.scene.image.WritableImage;
import javafx.stage.Stage;
import org.opencv.core.Core;
import org.opencv.core.Mat;
import org.opencv.core.MatOfDouble;
import org.opencv.highgui.HighGui;
import org.opencv.imgcodecs.Imgcodecs;
public class AddingNoise extends Application {
public void start(Stage stage) throws IOException {
//Loading the OpenCV core library
System.loadLibrary(Core.NATIVE_LIBRARY_NAME);
//Reading the Image from the file
String file ="D://images//elephant.jpg";
Mat src = Imgcodecs.imread(file);
System.out.println("Image Loaded");
//Creating destination matrix
Mat dst = new Mat(src.rows(), src.cols(), src.type());
//Creating a matrix for the noise
Mat noise = new Mat(src.rows(), src.cols(), src.type());
//Calculating the mean and standard deviation
MatOfDouble mean = new MatOfDouble();
MatOfDouble dev = new MatOfDouble();
Core.meanStdDev(src, mean, dev);
//Filling the noise matrix
Core.randn(noise, mean.get(0,0)[0], dev.get(0,0)[0]);
//Adding noise to the destination
Core.add(src, noise, dst);
//Converting matrix to JavaFX writable image
Image img = HighGui.toBufferedImage(dst);
WritableImage writableImage= SwingFXUtils.toFXImage((BufferedImage) img, null);
//Setting the image view
ImageView imageView = new ImageView(writableImage);
imageView.setX(10);
imageView.setY(10);
imageView.setFitWidth(575);
imageView.setPreserveRatio(true);
//Setting the Scene object
Group root = new Group(imageView);
Scene scene = new Scene(root, 595, 400);
stage.setTitle("Adding Noise Example");
stage.setScene(scene);
stage.show();
}
public static void main(String args[]) {
launch(args);
}
}输入图像
输出
执行上述程序后，将生成以下输出−
