我正在做一项任务，要求我们开发一个程序，对具有不同过滤器尺寸 3x3、5x5...11x11 的灰度图像执行平均过滤器
首先我用Java开发了一个矩阵类：
final public class Matrix {
private final int M; // number of rows
private final int N; // number of columns
private final double[][] data; // M-by-N array
// create M-by-N matrix of 0's
public Matrix(int M, int N) {
this.M = M;
this.N = N;
data = new double[M][N];
}
// create matrix based on 2d array
public Matrix(double [][] data) {
M = data.length;
N = data[0].length;
this.data = new double[M][N];
for (int i = 0; i < M; i++)
for (int j = 0; j < N; j++)
this.data[i][j] = data[i][j];
}
public static Matrix filter(int M, int N) {
Matrix A = new Matrix(M, N);
for (int i = 0; i < M; i++)
for (int j = 0; j < N; j++)
A.data[i][j] = (1.0/9.0);
return A;
}
// copy constructor
private Matrix(Matrix A) { this(A.data); }
// return C = A + B
public Matrix plus(Matrix B) {
Matrix A = this;
if (B.M != A.M || B.N != A.N) throw new RuntimeException("Illegal matrix dimensions.");
Matrix C = new Matrix(M, N);
for (int i = 0; i < M; i++)
for (int j = 0; j < N; j++)
C.data[i][j] = A.data[i][j] + B.data[i][j];
return C;
}
// return C = A - B
public Matrix minus(Matrix B) {
Matrix A = this;
if (B.M != A.M || B.N != A.N) throw new RuntimeException("Illegal matrix dimensions.");
Matrix C = new Matrix(M, N);
for (int i = 0; i < M; i++)
for (int j = 0; j < N; j++)
C.data[i][j] = A.data[i][j] - B.data[i][j];
return C;
}
public boolean eq(Matrix B) {
Matrix A = this;
if (B.M != A.M || B.N != A.N) throw new RuntimeException("Illegal matrix dimensions.");
for (int i = 0; i < M; i++)
for (int j = 0; j < N; j++)
if (A.data[i][j] != B.data[i][j]) return false;
return true;
}
// return C = A * B
public Matrix multiply(Matrix B) {
Matrix A = this;
if (A.N != B.M) throw new RuntimeException("Illegal matrix dimensions.");
Matrix C = new Matrix(A.M, B.N);
for (int i = 0; i < C.M; i++)
for (int j = 0; j < C.N; j++)
for (int k = 0; k < A.N; k++)
C.data[i][j] += (A.data[i][k] * B.data[k][j]);
return C;
}
public double average (){
double sum=0.0;
for (int i = 0; i < M; i++) {
for (int j = 0; j < N; j++) {
sum = sum + data[i][j];
}
}
return sum;
}
public void show() {
for (int i = 0; i < M; i++) {
for (int j = 0; j < N; j++)
System.out.printf("%9.4f ", data[i][j]);
System.out.println();
}
}
}
然后我开发了我的图像过滤应用程序，如下所示：
import java.awt.BorderLayout;
import java.awt.FlowLayout;
import java.awt.Image;
import java.awt.image.BufferedImage;
import java.awt.image.Raster;
import java.awt.image.WritableRaster;
import java.io.File;
import java.io.IOException;
import java.util.Scanner;
import javax.imageio.ImageIO;
import javax.swing.ImageIcon;
import javax.swing.JFrame;
import javax.swing.JLabel;
import javax.swing.JPanel;
/**
*
* @author Yousra
*/
public class ImgfilterApplication {
/**
* @param args the command line arguments
*/
public static void main(String[] args) {
System.out.println("Please Enter Your Image Path Here ...");
Scanner myscanner = new Scanner(System.in);
String path = myscanner.next();
BufferedImage img = getImage(path);
int filtersize = 3;
BufferedImage outimg = TDfilter(img, filtersize);
JFrame frame = new JFrame();
JLabel image = new JLabel(new ImageIcon("imageName.png"));
frame.getContentPane().setLayout(new FlowLayout());
frame.getContentPane().add(new JLabel(new ImageIcon(img)));
frame.getContentPane().add(new JLabel(new ImageIcon(outimg)));
frame.pack();
frame.setVisible(true);
}
public static BufferedImage TDfilter (BufferedImage img, int filtersize){
int w = img.getWidth();
int h = img.getHeight();
WritableRaster cr=img.getRaster();
WritableRaster wr=img.copyData(null);
double[][] imgarray = Img2D(img);
double[][] x = new double[filtersize][filtersize];
Matrix filter = Matrix.filter(filtersize, filtersize);
filter.show();
Matrix imgm = new Matrix(w,h);;
Matrix result;
for (int ii = 0; ii < w; ii++)
for (int jj = 0; jj < h; jj++) {
for (int i = ii; i < filtersize + ii; i++) {
for (int j = jj; j < filtersize + jj; j++) {
if (i - filtersize / 2 < 0 || i - filtersize / 2 >= w || j- filtersize / 2 < 0 || j- filtersize / 2 >= h) {
x[i-ii][j-jj] = 0;
// imgm = new Matrix(x);
} else {
x[i-ii][j-jj] = imgarray[i - filtersize / 2][j - filtersize / 2];
};
}
}
imgm = new Matrix(x);
result = imgm.multiply(filter);
double value = result.average();
wr.setSample(ii, jj, 0, value);
}
BufferedImage img2= new BufferedImage(w, h, img.getType());
img2.setData(wr);
return img2;
}
public static double [][] Img2D(BufferedImage img) {
int w = img.getWidth();
int h = img.getHeight();
double[][] imgarray = new double[w][h] ;
Raster raster = img.getData();
for (int i = 0; i < w; i++) {
for (int j = 0; j < h; j++) {
imgarray[i][j] = raster.getSample(i, j, 0);
}
}
return imgarray;
}
public static BufferedImage getImage(String imageName) {
try {
File input = new File(imageName);
BufferedImage image = ImageIO.read(input);
return image;
} catch (IOException ie) {
System.out.println("Error:" + ie.getMessage());
}
return null;
}
}
这假设会使图像更加模糊，但它会使其部分模糊，而其他部分则以随机模式呈现负片。你能帮忙吗:(