这篇文章主要介绍了java生成缩略图的方法,结合具体实例形式分析了java生成缩略图过程中所涉及的各种常见的图形处理技巧,需要的朋友可以参考下
本文实例讲述了java生成缩略图的方法。分享给大家供大家参考，具体如下：
package com.util;
import java.awt.image.BufferedImage;
import java.io.File;
import java.io.IOException;
import javax.imageio.ImageIO;
/**
* 生成压缩图
*
*/
public class ImageScale {
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;
// update by libra
double wt = w > width ? width : w;
double ht = h > height ? height : h;
scaleH = (double) wt / (double) width;
scaleV = (double) ht / (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
*/
public boolean scale(String source, String target, int width, int height) {
File f = new File(source);
try {
BufferedImage bi = ImageIO.read(f);
BufferedImage out = null;
ImageScale scal = new ImageScale();
int _width = bi.getWidth();// add
int _height = bi.getHeight();// add
int[] _arr = this.getImageWidthAndHeight(_width, _height, width,
height);// add
// out = scal.imageZoomOut(bi, width, height);
out = scal.imageZoomOut(bi, _arr[0], _arr[1]);
File t = new File(target);
ImageIO.write(out, "jpg", t);
return true;
} catch (IOException e) {
e.printStackTrace();
return false;
}
}
/**
* 得到放大或者缩小后的比例
*
* @param W
* 图片原宽
* @param H
* 原高
* @param tarW
* 转换后的宽
* @param zoom
* 放大还是缩小
* @return 返回宽和高的数组
*/
private static int[] getImageWidthAndHeight(int orgW, int orgH, int avW,
int avH) {
int width = 0;
int height = 0;
if (orgW > 0 && orgH > 0) {
if (orgW / orgH >= avW / avH) {
if (orgW > avW) {
width = avW;
height = (orgH * avW) / orgW;
} else {
width = orgW;
height = orgH;
}
System.out.println("++Widht:" + width + " Height" + height);
} else {
if (orgH > avH) {
height = avH;
width = (orgW * avH) / orgH;
} else {
width = orgW;
height = orgH;
}
System.out.println("++Widht:" + width + " Height" + height);
}
}
int[] arr = new int[2];
arr[0] = width;
arr[1] = height;
// long start = System.currentTimeMillis();
// int width = 0;
// int height = 0;
// if ((W / tarW) >= (H / tarH)) {// 宽的缩小比例大于高的
// width = tarW;
// height = H * tarW / W;
// System.out.println(width + " " + height);
// } else {
// height = tarH;
// width = W * tarH / H;
// System.out.println(width + " " + height);
// }
// int[] arr = new int[2];
// arr[0] = width;
// arr[1] = height;
// long end = System.currentTimeMillis();
// System.out.println("宽高处理：" + (end - start));
return arr;
}
public void picscale(String source, String target, int w, int h) {
File f = new File(source);
int width = 0;
int height = 0;
try {
BufferedImage bi = ImageIO.read(f);
int[] arr = getImageWidthAndHeight(bi.getWidth(), bi.getHeight(),
w, h);
width = arr[0];
height = arr[1];
BufferedImage out = null;
ImageScale scal = new ImageScale();
out = scal.imageZoomOut(bi, width, height);
File t = new File(target);
ImageIO.write(out, "jpg", t);
} catch (IOException e) {
e.printStackTrace();
}
}
/**
*
*调用scale(源文件路径，保存路径，最大宽，最大高)
*
*
*/
public static void main(String[] args) {
ImageScale is = new ImageScale();
long start = System.currentTimeMillis();
is.scale("D:/nie.jpg", "D:/t6.jpg", 250, 194);
long end = System.currentTimeMillis();
System.out.println("时间：" + (end - start));
}
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