今天在网上看到了一篇关于JAVA图像处理的文章，博主贴出了一个处理类：特点是高品质缩小，具体代码如下：
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.FileOutputStream;
import java.io.IOException;
import javax.imageio.ImageIO;
public class ImageScale 
{
private int width;
private int height;
private int scaleWidth;
double support = (double) 3.0;
double[] contrib;
double[] normContrib;
double[] tmpContrib;
int startContrib, stopContrib;
int nDots;
int nHalfDots;
public BufferedImage imageZoomOut(BufferedImage srcBufferImage, int w, int h, boolean lockScale) {
width = srcBufferImage.getWidth();
height = srcBufferImage.getHeight();
scaleWidth = w;
if (lockScale) {
h = w * height / width;
}
if (DetermineResultSize(w, h) == 1) {
return srcBufferImage;
}
CalContrib();
BufferedImage pbOut = HorizontalFiltering(srcBufferImage, w);
BufferedImage pbFinalOut = VerticalFiltering(pbOut, h);
return pbFinalOut;
}
/** *//**
* 决定图像尺寸
*/
private int DetermineResultSize(int w, int h) {
double scaleH, scaleV;
scaleH = (double) w / (double) width;
scaleV = (double) h / (double) height;
// 需要判断一下scaleH，scaleV，不做放大操作
if (scaleH >= 1.0 && scaleV >= 1.0) {
return 1;
}
return 0;
} // end of DetermineResultSize()
private double Lanczos(int i, int inWidth, int outWidth, double Support) {
double x;
x = (double) i * (double) outWidth / (double) inWidth;
return Math.sin(x * Math.PI) / (x * Math.PI) * Math.sin(x * Math.PI / Support) / (x * Math.PI / Support);
} // end of Lanczos()
//
// Assumption: same horizontal and vertical scaling factor
//
private void CalContrib() {
nHalfDots = (int) ((double) width * support / (double) scaleWidth);
nDots = nHalfDots * 2 + 1;
try {
contrib = new double[nDots];
normContrib = new double[nDots];
tmpContrib = new double[nDots];
} catch (Exception e) {
System.out.println("init contrib,normContrib,tmpContrib" + e);
}
int center = nHalfDots;
contrib[center] = 1.0;
double weight = 0.0;
int i = 0;
for (i = 1; i <= center; i++) {
contrib[center + i] = Lanczos(i, width, scaleWidth, support);
weight += contrib[center + i];
}
for (i = center - 1; i >= 0; i--) {
contrib[i] = contrib[center * 2 - i];
}
weight = weight * 2 + 1.0;
for (i = 0; i <= center; i++) {
normContrib[i] = contrib[i] / weight;
}
for (i = center + 1; i < nDots; i++) {
normContrib[i] = normContrib[center * 2 - i];
}
} // end of CalContrib()
// 处理边缘
private void CalTempContrib(int start, int stop) {
double weight = 0;
int i = 0;
for (i = start; i <= stop; i++) {
weight += contrib[i];
}
for (i = start; i <= stop; i++) {
tmpContrib[i] = contrib[i] / weight;
}
} // end of CalTempContrib()
private int GetRedValue(int rgbValue) {
int temp = rgbValue & 0x00ff0000;
return temp >> 16;
}
private int GetGreenValue(int rgbValue) {
int temp = rgbValue & 0x0000ff00;
return temp >> 8;
}
private int GetBlueValue(int rgbValue) {
return rgbValue & 0x000000ff;
}
private int ComRGB(int redValue, int greenValue, int blueValue) {
return (redValue << 16) + (greenValue << 8) + blueValue;
}
// 行水平滤波
private int HorizontalFilter(BufferedImage bufImg, int startX, int stopX, int start, int stop, int y,
double[] pContrib) {
double valueRed = 0.0;
double valueGreen = 0.0;
double valueBlue = 0.0;
int valueRGB = 0;
int i, j;
for (i = startX, j = start; i <= stopX; i++, j++) {
valueRGB = bufImg.getRGB(i, y);
valueRed += GetRedValue(valueRGB) * pContrib[j];
valueGreen += GetGreenValue(valueRGB) * pContrib[j];
valueBlue += GetBlueValue(valueRGB) * pContrib[j];
}
valueRGB = ComRGB(Clip((int) valueRed), Clip((int) valueGreen), Clip((int) valueBlue));
return valueRGB;
} // end of HorizontalFilter()
// 图片水平滤波
private BufferedImage HorizontalFiltering(BufferedImage bufImage, int iOutW) {
int dwInW = bufImage.getWidth();
int dwInH = bufImage.getHeight();
int value = 0;
BufferedImage pbOut = new BufferedImage(iOutW, dwInH, BufferedImage.TYPE_INT_RGB);
for (int x = 0; x < iOutW; x++) {
int startX;
int start;
int X = (int) (((double) x) * ((double) dwInW) / ((double) iOutW) + 0.5);
int y = 0;
startX = X - nHalfDots;
if (startX < 0) {
startX = 0;
start = nHalfDots - X;
} else {
start = 0;
}
int stop;
int stopX = X + nHalfDots;
if (stopX > (dwInW - 1)) {
stopX = dwInW - 1;
stop = nHalfDots + (dwInW - 1 - X);
} else {
stop = nHalfDots * 2;
}
if (start > 0 || stop < nDots - 1) {
CalTempContrib(start, stop);
for (y = 0; y < dwInH; y++) {
value = HorizontalFilter(bufImage, startX, stopX, start, stop, y, tmpContrib);
pbOut.setRGB(x, y, value);
}
} else {
for (y = 0; y < dwInH; y++) {
value = HorizontalFilter(bufImage, startX, stopX, start, stop, y, normContrib);
pbOut.setRGB(x, y, value);
}
}
}
return pbOut;
} // end of HorizontalFiltering()
private int VerticalFilter(BufferedImage pbInImage, int startY, int stopY, int start, int stop, int x,
double[] pContrib) {
double valueRed = 0.0;
double valueGreen = 0.0;
double valueBlue = 0.0;
int valueRGB = 0;
int i, j;
for (i = startY, j = start; i <= stopY; i++, j++) {
valueRGB = pbInImage.getRGB(x, i);
valueRed += GetRedValue(valueRGB) * pContrib[j];
valueGreen += GetGreenValue(valueRGB) * pContrib[j];
valueBlue += GetBlueValue(valueRGB) * pContrib[j];
}
valueRGB = ComRGB(Clip((int) valueRed), Clip((int) valueGreen), Clip((int) valueBlue));
// System.out.println(valueRGB);
return valueRGB;
} // end of VerticalFilter()
private BufferedImage VerticalFiltering(BufferedImage pbImage, int iOutH) {
int iW = pbImage.getWidth();
int iH = pbImage.getHeight();
int value = 0;
BufferedImage pbOut = new BufferedImage(iW, iOutH, BufferedImage.TYPE_INT_RGB);
for (int y = 0; y < iOutH; y++) {
int startY;
int start;
int Y = (int) (((double) y) * ((double) iH) / ((double) iOutH) + 0.5);
startY = Y - nHalfDots;
if (startY < 0) {
startY = 0;
start = nHalfDots - Y;
} else {
start = 0;
}
int stop;
int stopY = Y + nHalfDots;
if (stopY > (int) (iH - 1)) {
stopY = iH - 1;
stop = nHalfDots + (iH - 1 - Y);
} else {
stop = nHalfDots * 2;
}
if (start > 0 || stop < nDots - 1) {
CalTempContrib(start, stop);
for (int x = 0; x < iW; x++) {
value = VerticalFilter(pbImage, startY, stopY, start, stop, x, tmpContrib);
pbOut.setRGB(x, y, value);
}
} else {
for (int x = 0; x < iW; x++) {
value = VerticalFilter(pbImage, startY, stopY, start, stop, x, normContrib);
pbOut.setRGB(x, y, value);
}
}
}
return pbOut;
} // end of VerticalFiltering()
int Clip(int x) {
if (x < 0)
return 0;
if (x > 255)
return 255;
return x;
}
public static void main(String[] args) throws IOException {
ImageScale is = new ImageScale();
String path = "D:\\My Documents\\My Pictures\\pictrue\\";
BufferedImage image1 = ImageIO.read(new File(path + "test.jpg"));
int w = 200, h = 400;
BufferedImage image2 = is.imageZoomOut(image1, w, h, true);
FileOutputStream out = new FileOutputStream(path + "test_2.jpg");
ImageIO.write(image2, "jpeg", out);
}
}
上面的代码中，本人做了一点小改进：imageZoomOut方法中，添加了一个lockScale参数，如果为true则表明保持纵横比。
程序运行的效果如下：
test.jpg（原图）：
test_2.jpg（程序生成的图片）：
