图像处理之高斯金字塔
一：图像金字塔基本操作
对一张图像不断的模糊之后向下采样，得到不同分辨率的图像，同时每次得到的
新的图像宽与高是原来图像的1/2, 最常见就是基于高斯的模糊之后采样，得到的
一系列图像称为高斯金字塔。
高斯金字塔不同(DoG)又称为拉普拉斯金字塔，其计算公式如下：
L(i) = G(i) – expand(G(i+1))
第i层拉普拉斯金字塔是由第i层高斯金字塔减去第i+1层高斯金字塔expand之后得到。
本文得到的DoG(Difference of Gaussian)结果如下：
二：关键代码解析
金字塔reduce操作实现代码如下：
private BufferedImage pyramidReduce(BufferedImage src) {
int width = src.getWidth();
int height = src.getHeight();
BufferedImage dest = createSubCompatibleDestImage(src, null);
int[] inPixels = new int[width*height];
int ow = width/2;
int oh = height/2;
int[] outPixels = new int[ow*oh];
getRGB(src, 0, 0, width, height, inPixels );
int inRow=0, inCol = 0, index = 0, oudex =0, ta = 0;
float[][] keneralData = this.getHVGaussianKeneral();
for(int row=0; row= height) {
inRow = 0;
}
if(inCol >= width) {
inCol = 0;
}
float sumRed = 0, sumGreen = 0, sumBlue = 0;
for(int subRow = -2; subRow <= 2; subRow++) {
int inRowOff = inRow + subRow;
if(inRowOff >= height || inRowOff < 0) {
inRowOff = 0;
}
for(int subCol = -2; subCol <= 2; subCol++) {
int inColOff = inCol + subCol;
if(inColOff >= width || inColOff < 0) {
inColOff = 0;
}
index = inRowOff * width + inColOff;
ta = (inPixels[index] >> 24) & 0xff;
int red = (inPixels[index] >> 16) & 0xff;
int green = (inPixels[index] >> 8) & 0xff;
int blue = inPixels[index] & 0xff;
sumRed += keneralData[subRow + 2][subCol + 2] * red;
sumGreen += keneralData[subRow + 2][subCol + 2] * green;
sumBlue += keneralData[subRow + 2][subCol + 2] * blue;
}
}
oudex = row * ow + col;
outPixels[oudex] = (ta << 24) | (clamp(sumRed) << 16) | (clamp(sumGreen) << 8) | clamp(sumBlue);
}
}
setRGB( dest, 0, 0, ow, oh, outPixels );
return dest;
} public BufferedImage pyramidExpand(BufferedImage src) {
int width = src.getWidth();
int height = src.getHeight();
int[] inPixels = new int[width*height];
getRGB(src, 0, 0, width, height, inPixels );
int ow = 2*width;
int oh =2*height;
int[] outPixels = new int[ow * oh];
int index = 0, outdex = 0, ta = 0;
float[][] keneralData = this.getHVGaussianKeneral();
BufferedImage dest = createTwiceCompatibleDestImage(src, null);
for(int row=0; row 0) {
continue;
}
if(srcRow >= height || srcRow < 0) {
srcRow = 0;
}
for(int subCol = -2; subCol <= 2; subCol++) {
double srcColOff = (col + subCol)/2.0;
j = Math.floor(srcColOff);
t = srcColOff - j;
if(t > 0) {
continue;
}
if(srcColOff >= width || srcColOff < 0) {
srcColOff = 0;
}
index = (int)(srcRow * width + srcColOff);
ta = (inPixels[index] >> 24) & 0xff;
int red = (inPixels[index] >> 16) & 0xff;
int green = (inPixels[index] >> 8) & 0xff;
int blue = inPixels[index] & 0xff;
sumRed += keneralData[subRow + 2][subCol + 2] * red;
sumGreen += keneralData[subRow + 2][subCol + 2] * green;
sumBlue += keneralData[subRow + 2][subCol + 2] * blue;
}
}
outdex = row * ow + col;
outPixels[outdex] = (ta << 24) | (clamp(4.0f * sumRed) << 16) | (clamp(4.0f * sumGreen) << 8) | clamp(4.0f * sumBlue);
// outPixels[outdex] = (ta << 24) | (clamp(sumRed) << 16) | (clamp(sumGreen) << 8) | clamp(sumBlue);
}
}
setRGB( dest, 0, 0, ow, oh, outPixels );
return dest;
} 操作不是reduce的可逆操作。
关于什么是卷积，高斯滤波请参见博客上的其它相关文章。
高斯金字塔全部算法源代码如下：
package com.gloomyfish.image.pyramid;
import java.awt.image.BufferedImage;
import java.awt.image.ColorModel;
public class PyramidAlgorithm extends GaussianFilter {
private float a;
public PyramidAlgorithm() {
a = 0.4f;
}
public void setParameter(float p) {
this.a = p;
}
public BufferedImage[] pyramidDown(BufferedImage src, int level) {
BufferedImage[] imagePyramids = new BufferedImage[level + 1];
imagePyramids[0] = src;
for(int i=1; i ewidth) ? ewidth : width;
height = (height > expandImage.getHeight()) ? expandImage.getHeight():height;
System.out.println(" width = " + width + " expand width = " + ewidth);
int[] reducePixels = new int[width*height];
int[] expandPixels = new int[width*height];
int[] laPixels = new int[width*height];
getRGB( reduceImages[i-1], 0, 0, width, height, reducePixels);
getRGB( expandImage, 0, 0, width, height, expandPixels );
int index = 0;
int er = 0, eg = 0, eb = 0;
for(int row=0; row> 24) & 0xff;
tr = (reducePixels[index] >> 16) & 0xff;
tg = (reducePixels[index] >> 8) & 0xff;
tb = reducePixels[index] & 0xff;
ta = (expandPixels[index] >> 24) & 0xff;
er = (expandPixels[index] >> 16) & 0xff;
eg = (expandPixels[index] >> 8) & 0xff;
eb = expandPixels[index] & 0xff;
tr = tr - er;
tg = tg - eg;
tb = tb - eb;
laPixels[index] = (ta << 24) | (clamp(tr) << 16) | (clamp(tg) << 8) | clamp(tb);
}
}
setRGB( laplaciImages[i-1], 0, 0, width, height, laPixels );
}
return laplaciImages;
}
private BufferedImage pyramidReduce(BufferedImage src) {
int width = src.getWidth();
int height = src.getHeight();
BufferedImage dest = createSubCompatibleDestImage(src, null);
int[] inPixels = new int[width*height];
int ow = width/2;
int oh = height/2;
int[] outPixels = new int[ow*oh];
getRGB(src, 0, 0, width, height, inPixels );
int inRow=0, inCol = 0, index = 0, oudex =0, ta = 0;
float[][] keneralData = this.getHVGaussianKeneral();
for(int row=0; row= height) {
inRow = 0;
}
if(inCol >= width) {
inCol = 0;
}
float sumRed = 0, sumGreen = 0, sumBlue = 0;
for(int subRow = -2; subRow <= 2; subRow++) {
int inRowOff = inRow + subRow;
if(inRowOff >= height || inRowOff < 0) {
inRowOff = 0;
}
for(int subCol = -2; subCol <= 2; subCol++) {
int inColOff = inCol + subCol;
if(inColOff >= width || inColOff < 0) {
inColOff = 0;
}
index = inRowOff * width + inColOff;
ta = (inPixels[index] >> 24) & 0xff;
int red = (inPixels[index] >> 16) & 0xff;
int green = (inPixels[index] >> 8) & 0xff;
int blue = inPixels[index] & 0xff;
sumRed += keneralData[subRow + 2][subCol + 2] * red;
sumGreen += keneralData[subRow + 2][subCol + 2] * green;
sumBlue += keneralData[subRow + 2][subCol + 2] * blue;
}
}
oudex = row * ow + col;
outPixels[oudex] = (ta << 24) | (clamp(sumRed) << 16) | (clamp(sumGreen) << 8) | clamp(sumBlue);
}
}
setRGB( dest, 0, 0, ow, oh, outPixels );
return dest;
}
public BufferedImage createSubCompatibleDestImage(BufferedImage src, ColorModel dstCM) {
if ( dstCM == null )
dstCM = src.getColorModel();
return new BufferedImage(dstCM, dstCM.createCompatibleWritableRaster(src.getWidth()/2, src.getHeight()/2), dstCM.isAlphaPremultiplied(), null);
}
public BufferedImage createTwiceCompatibleDestImage(BufferedImage src, ColorModel dstCM) {
if ( dstCM == null )
dstCM = src.getColorModel();
return new BufferedImage(dstCM, dstCM.createCompatibleWritableRaster(src.getWidth()*2, src.getHeight()*2), dstCM.isAlphaPremultiplied(), null);
}
public BufferedImage pyramidExpand(BufferedImage src) {
int width = src.getWidth();
int height = src.getHeight();
int[] inPixels = new int[width*height];
getRGB(src, 0, 0, width, height, inPixels );
int ow = 2*width;
int oh =2*height;
int[] outPixels = new int[ow * oh];
int index = 0, outdex = 0, ta = 0;
float[][] keneralData = this.getHVGaussianKeneral();
BufferedImage dest = createTwiceCompatibleDestImage(src, null);
for(int row=0; row 0) {
continue;
}
if(srcRow >= height || srcRow < 0) {
srcRow = 0;
}
for(int subCol = -2; subCol <= 2; subCol++) {
double srcColOff = (col + subCol)/2.0;
j = Math.floor(srcColOff);
t = srcColOff - j;
if(t > 0) {
continue;
}
if(srcColOff >= width || srcColOff < 0) {
srcColOff = 0;
}
index = (int)(srcRow * width + srcColOff);
ta = (inPixels[index] >> 24) & 0xff;
int red = (inPixels[index] >> 16) & 0xff;
int green = (inPixels[index] >> 8) & 0xff;
int blue = inPixels[index] & 0xff;
sumRed += keneralData[subRow + 2][subCol + 2] * red;
sumGreen += keneralData[subRow + 2][subCol + 2] * green;
sumBlue += keneralData[subRow + 2][subCol + 2] * blue;
}
}
outdex = row * ow + col;
outPixels[outdex] = (ta << 24) | (clamp(4.0f * sumRed) << 16) | (clamp(4.0f * sumGreen) << 8) | clamp(4.0f * sumBlue);
// outPixels[outdex] = (ta << 24) | (clamp(sumRed) << 16) | (clamp(sumGreen) << 8) | clamp(sumBlue);
}
}
setRGB( dest, 0, 0, ow, oh, outPixels );
return dest;
}
}
会有问题，使用时请自己处理吧。
UI实现源代码如下：
package com.gloomyfish.image.pyramid;
import java.awt.BorderLayout;
import java.awt.Dimension;
import java.awt.FlowLayout;
import java.awt.Graphics;
import java.awt.MediaTracker;
import java.awt.event.ActionEvent;
import java.awt.event.ActionListener;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;
import javax.imageio.ImageIO;
import javax.swing.JButton;
import javax.swing.JComponent;
import javax.swing.JFileChooser;
import javax.swing.JFrame;
import javax.swing.JPanel;
public class PyramidDemoUI extends JComponent implements ActionListener {
/**
*
*/
private static final long serialVersionUID = 1L;
private JButton upButton;
private JButton downButton;
private BufferedImage[] reduceImages;
private BufferedImage[] expandImages;
private BufferedImage sourceImage;
private Dimension mySize;
private MediaTracker tracker;
public PyramidDemoUI(File f)
{
initComponents(f);
}
private void initComponents(File f)
{
// TODO Auto-generated method stub
try {
sourceImage = ImageIO.read(f);
} catch (IOException e1) {
e1.printStackTrace();
}
tracker = new MediaTracker(this);
tracker.addImage(sourceImage, 1);
// blocked 10 seconds to load the image data
try {
if (!tracker.waitForID(1, 10000)) {
System.out.println("Load error.");
System.exit(1);
}// end if
} catch (InterruptedException e) {
e.printStackTrace();
System.exit(1);
}// end catch
JPanel btnPanel = new JPanel();
btnPanel.setLayout(new FlowLayout(FlowLayout.RIGHT));
upButton = new JButton("Laplacian Pyramid");
downButton = new JButton("Pyramid Down");
upButton.addActionListener(this);
downButton.addActionListener(this);
btnPanel.add(upButton);
btnPanel.add(downButton);
mySize = new Dimension(800, 800);
JFrame mainFrame = new JFrame("Pyramid Demo - Gloomyfish");
mainFrame.getContentPane().setLayout(new BorderLayout());
mainFrame.getContentPane().add(this, BorderLayout.CENTER);
mainFrame.getContentPane().add(btnPanel, BorderLayout.SOUTH);
mainFrame.setDefaultCloseOperation(JFrame.EXIT_ON_CLOSE);
mainFrame.pack();
mainFrame.setVisible(true);
}
@Override
public Dimension getPreferredSize() {
return mySize;
}
@Override
protected void paintComponent(Graphics g)
{
// g.drawImage(sourceImage, 10, 10, sourceImage.getWidth(), sourceImage.getHeight(), null);
int width = 10;
// if(reduceImages != null) {
// for(int i=1; i