這篇文章主要介紹了java產生縮圖的方法,結合具體實例形式分析了java產生縮圖過程中所涉及的各種常見的圖形處理技巧,需要的朋友可以參考下
本文實例講述了java生成縮圖的方法。具體如下:
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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