现在web应用经常会用到缩略图。然后一旦生成的缩略图小于100px * 100px,一些常用的java包，生成的图片确实有点惨不忍睹。 现在介绍使用Jmagick的使用，可以生成质量很好的缩略图，当然还有其他很多图像处理的方法。 首先jmagick（http://www.yeo.id.au/jmagick/）是ImageMagick（http://www.imagemagick.org/）的java 应用的接口。所以要先安装ImageMagick应用程序，你的java应用才能使用,在主页上你可以轻松找到下载的链接。 1。下载jmagick,imagemagick 2.安装ImageMagick，网站上有安装方法（windows,unnix）,我只在win上做了安装，安装以后把安装目录下所有的dll文件copy到windows/system32/目录下。 3。下载的jmagick包含jmagick.jar,jmagick.dll文件，jmagick.dll需要copy到windows/system32/目录下。 4。web应用如果部署到tomcat下，那么最好在catalina.bat文件中改变如下设置set JAVA_OPTS=%JAVA_OPTS% -Xms256M -Xmx768M -XX:MaxPermSize=128M -Djava.util.logging.manager=org.apache.juli.ClassLoaderLogManager -Djava.util.logging.config.file="${catalina.base}\conf\logging.properties" 避免heap溢出的问题，参数看你自己的机器而定。（ -Xms256M -Xmx768M -XX:MaxPermSize=128M ） 5。还要注意如果部署到web应用，你在使用的class里面需要 System.setProperty("jmagick.systemclassloader","no"); 要不然会报出UnsatisfiedLinkError: no JMagick in java.library.path. 实例如下： public void resize(String picFrom,String picTo) {
try {
// Resize
ImageInfo info = new ImageInfo(picFrom);
MagickImage image = new MagickImage(new ImageInfo(picFrom));
MagickImage scaled = image.scaleImage(100, 86);//小图片文件的大小.
scaled.setFileName(picTo);
scaled.writeImage(info); } catch(MagickApiException ex) { } catch(MagickException ex) { }
}注：linux系统下，需要下载另外的包
by：阿飞
2006-06-03
try {
// Resize
ImageInfo info = new ImageInfo(picFrom);
MagickImage image = new MagickImage(new ImageInfo(picFrom));
MagickImage scaled = image.scaleImage(100, 86);//小图片文件的大小.
scaled.setFileName(picTo);
scaled.writeImage(info); } catch(MagickApiException ex) { } catch(MagickException ex) { }
}注：linux系统下，需要下载另外的包
by：阿飞
2006-06-03
// Resize
System.setProperty("jmagick.systemclassloader","no");
ImageInfo info = new ImageInfo(sourceFileName);
MagickImage image = new MagickImage(info);
MagickImage scaled = image.scaleImage(w, h);//小图片文件的大小.
scaled.setFileName(destFile);
scaled.writeImage(info); } catch(MagickApiException ex) {
System.out.println(ex); } catch(MagickException ex) {
System.out.println(ex);
}
}
private int width;
private int height;
private int scaleWidth;
double support = (double) 3.0;
double PI = (double) 3.14159265358978;
double[] contrib;
double[] normContrib;
double[] tmpContrib;
int startContrib, stopContrib;
int nDots;
int nHalfDots; /**
* Start:
* Use Lanczos filter to replace the original algorithm for image scaling. Lanczos improves quality of the scaled image
* modify by :blade
* */
public BufferedImage imageZoomOut(BufferedImage srcBufferImage,int w, int h) {
width = srcBufferImage.getWidth();
height = srcBufferImage.getHeight();
scaleWidth = w; 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 * PI) / (x * PI) * Math.sin(x * PI / Support)
/ (x * 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];
// System.out.println(valueRed+"->"+Clip((int)valueRed)+"<-");
//
// System.out.println(valueGreen+"->"+Clip((int)valueGreen)+"<-");
// System.out.println(valueBlue+"->"+Clip((int)valueBlue)+"<-"+"-->");
} 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;
} /**
* End:
* Use Lanczos filter to replace the original algorithm for image scaling. Lanczos improves quality of the scaled image
* modify by :blade
* */
}
An unrecoverable stack overflow has occurred.
#
# An unexpected error has been detected by HotSpot Virtual Machine:
#
# EXCEPTION_STACK_OVERFLOW (0xc00000fd) at pc=0x100d8a05, pid=3740, tid=3664
#
# Java VM: Java HotSpot(TM) Client VM (1.5.0_07-b03 mixed mode, sharing)
# Problematic frame:
# C [CORE_RL_magick_.dll+0xd8a05]
#
# An error report file with more information is saved as hs_err_pid3740.log
#
# If you would like to submit a bug report, please visit:
# http://java.sun.com/webapps/bugreport/crash.jsp
#这是为什么呢