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java生成高清缩略图

之前写过一个java生成缩略图的算法,最近使用发现大图片缩小以后,效果很差。特意搞到一个生成高清缩略图的算法。相对清晰不少,不过比使用photoshop软件生成的缩略图还是会差一点,不仔细对比,是看不出来的。

高清,都是相对的。这个生成以后效果还不错。

import java.awt.image.BufferedImage;

public class ImgHigh {
	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
	 * */

}

外部的用法

BufferedImage outImage = new ImgHigh().imageZoomOut(src, scaledW, scaledH);
然后把outImage这个流保存为图片就好了。

this.saveAsFile(thumb, outImage, quality);

quality为图片质量,经过测试采用90%的质量,图片看起来不会有太大差别,但是文件会小到1/3。

附保存图片算法

public void saveAsFile(String outFileName, BufferedImage outImage,
			int quality) {
		BufferedOutputStream out;
		try {
			out = new BufferedOutputStream(

			new FileOutputStream(outFileName));

			JPEGImageEncoder encoder = JPEGCodec.createJPEGEncoder(out);

			JPEGEncodeParam param = encoder

			.getDefaultJPEGEncodeParam(outImage);

			quality = Math.max(0, Math.min(quality, 100));

			param.setQuality((float) quality / 100.0f, false);

			encoder.setJPEGEncodeParam(param);

			encoder.encode(outImage);

			out.close();
		} catch (Exception e) {
			// TODO Auto-generated catch block
			e.printStackTrace();
		}

	}

具体缩略图缩小算法,请参考 http://java-er.com/blog/java-img-suo/


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