图像处理基本算法 java代码

import java.awt.Image; import java.awt.image.BufferedImage; import java.awt.image.ColorConvertOp; import java.awt.image.ColorModel; import java.awt.image.MemoryImageSource; import java.awt.image.PixelGrabber; import java.io.File; import java.io.IOException; import java.util.Arrays; import java.awt.BorderLayout; import java.awt.Component; import java.awt.Dimension; import java.awt.Graphics2D; import java.awt.Image; import java.awt.Component.*; import java.awt.event.ActionEvent; import java.awt.event.ActionListener; import java.awt.image.BufferedImage; import java.awt.image.ColorModel; import java.awt.image.MemoryImageSource; import java.awt.image.PixelGrabber; import javax.imageio.ImageIO; import javax.swing.ImageIcon; import javax.swing.JFrame; import javax.swing.JScrollPane; import javax.swing.JTextArea; import javax.swing.SwingUtilities; import java.awt.Color; import java.awt.Graphics2D; import java.awt.image.BufferedImage; import java.awt.*; import java.awt.event.*; import javax.swing.*; public class sharp extends /*Component*/ JFrame { public static int[] histgray = new int[256*256]; public static int[] histsharp =new int[256*256]; public static int[] histbalance =new int[256*256]; public int[] grayImage() throws IOException{ File file = new File("1.jpg"); // File file = new File("D:\\学习\\数字图像处理\\homework1\\1.jpg"); BufferedImage image = ImageIO.read(file); int width = image.getWidth(); int height = image.getHeight(); int[] pix = new int[width*height]; PixelGrabber pg=null; try{ pg = new PixelGrabber(image, 0, 0, width, height, pix, 0, width); if(pg.grabPixels()!=true) try{ throw new java.awt.AWTException("pg error"+pg.status()); }catch(Exception eq){ eq.printStackTrace(); } } catch(Exception ex){ ex.printStackTrace(); } int[]grayArray=new int[height*width]; ColorModel colorModel=ColorModel.getRGBdefault(); int i ,j,k,r,g,b; for(i = 0; i < height;i++){ for(j = 0;j < width;j++){ k = i*width+j; r = colorModel.getRed(pix[k]); g = colorModel.getGreen(pix[k]); b = colorModel.getBlue(pix[k]); int gray=(int)(r*0.3+g*0.59+b*0.11); r=g=b=gray; // System.out.println(r); grayArray[i*width+j]= (255 << 24) | (r << 16) | (g << 8 )| b; histgray[i*width+j] = gray; } } return grayArray; /* BufferedImage grayImage = new BufferedImage(width, height, BufferedImage.TYPE_INT_RGB); for(int ii= 0 ; ii < width ; ii++){ for(int jj = 0 ; jj < height; jj++){ //int rgb = image.getRGB(i, j); grayImage.setRGB(ii, jj, grayArray[ii*width+jj]); } } File newFile = new File("D:\\1.bmp"); ImageIO.write(grayImage, "bmp", newFile); } */ } private void showImage(int[] srcPixArray){ int width=256; int height=256; final Image pic=createImage(new MemoryImageSource(width,height,srcPixArray,0,width)); ImageIcon ic=new ImageIcon(pic); // final String title1 = "灰度图像"; SwingUtilities.invokeLater(new Runnable(){ public void run(){ new ShowImage(pic).setVisible(true); } }); } public static int[] sharpFiltering(int pix[],int hist[]) { int w=256; int h=256; int newpix[] = new int[w*h]; int[] temp = new int[9]; ColorModel cm = ColorModel.getRGBdefault(); int r=0; for(int y=0; y<h; y++) { for(int x=0; x<w; x++) { if(x!=0 && x!=w-1 && y!=0 && y!=h-1) { //g = median[(x-1,y-1) + f(x,y-1)+ f(x+1,y-1) // + f(x-1,y) + f(x,y) + f(x+1,y) // + f(x-1,y+1) + f(x,y+1) + f(x+1,y+1)] temp[0] = cm.getRed(pix[x-1+(y-1)*w]); temp[1] = cm.getRed(pix[x+(y-1)*w]); temp[2] = cm.getRed(pix[x+1+(y-1)*w]); temp[3] = cm.getRed(pix[x-1+(y)*w]); temp[4] = cm.getRed(pix[x+(y)*w]); temp[5] = cm.getRed(pix[x+1+(y)*w]); temp[6] = cm.getRed(pix[x-1+(y+1)*w]); temp[7] = cm.getRed(pix[x+(y+1)*w]); temp[8] = cm.getRed(pix[x+1+(y+1)*w]); r = (int)(9.0/(1.0/temp[0]+1.0/temp[1]+1.0/temp[2]+1.0/temp[3]+1.0/temp[4]+1.0/temp[5]+1.0/temp[6]+1.0/temp[7]+1.0/temp[8])); if (r>255) r=255; temp[4] = r; newpix[y*w+x] = 255<<24 | r<<16 | r<<8 |r; histbalance[y*w+x] =(int) r; // System.out.println( histmedian[y*w+x]+"sdfsdf"); } else { newpix[y*w+x] = pix[y*w+x]; histbalance[y*w+x] =hist[y*w+x]; // System.out.println( histmedian[y*w+x]); } } } return newpix; } private Histogram histogram=new Histogram(); private JFrame histogramFrame=new JFrame(); // private JTextArea jta; public int[] laplace2DFileter(int []data, int[] hist){ int width = 256; int height = 256; int r=0; int filterData[]=new int[data.length]; int min=10000; int max=-10000; ColorModel cm = ColorModel.getRGBdefault(); int[] temp = new int[9]; for(int i=0;i<height;i++){ for(int j=0;j<width;j++){ if(i==0 || i==height-1 || j==0 || j==width-1){ filterData[i*width+j]=hist[i*width+j]; histsharp[i*width+j] = hist[i*width+j]; } else { temp[0] = cm.getRed(data[j-1+(i-1)*width]); temp[1] = cm.getRed(data[j+(i-1)*width]); temp[2] = cm.getRed(data[j+1+(i-1)*width]); temp[3] = cm.getRed(data[j-1+(i)*width]); temp[4] = cm.getRed(data[j+(i)*width]); temp[5] = cm.getRed(data[j+1+(i)*width]); temp[6] = cm.getRed(data[j-1+(i+1)*width]); temp[7] = cm.getRed(data[j+(i+1)*width]); temp[8] = cm.getRed(data[j+1+(i+1)*width]); r = 8*temp[4]-temp[0]-temp[1]-temp[2]-temp[3]-temp[5]-temp[6]-temp[7]-temp[8]; filterData[i*width+j] = r+20*temp[4]; histsharp[i*width+j] = r+temp[4]; } if(filterData[i*width+j]<min) min=filterData[i*width+j]; if(filterData[i*width+j]>max) max=filterData[i*width+j]; } } // System.out.println("max: "+max); // System.out.println("min: "+min); for(int i=0;i<width*height;i++){ filterData[i]=(filterData[i]-min)*255/(max-min); histsharp[i] = filterData[i]; } for(int i=0;i<width*height;i++){ filterData[i]=255<<24 | filterData[i]<<16 | filterData[i]<<8 | filterData[i]; } return filterData; } public void MultipelWindowsDemo(int[] count){ // JScrollPane scrollPane=new JScrollPane(jta=new JTextArea()); // scrollPane.setPreferredSize(new Dimension(300,200)); // jta.setWrapStyleWord(true); // jta.setLineWrap(true); // this.getContentPane().add(scrollPane,BorderLayout.CENTER); // this.getContentPane().add(jbtShowHistogram,BorderLayout.SOUTH); // jbtShowHistogram.addActionListener(this);