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图像处理之错切变换

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图像处理之错切变换

一:基本数学知识:

图像错切变换在图像几何形变方面很实用,常见的错切变换分为X方向与Y方向的

错切变换。相应的数学矩阵分别例如以下:

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依据上述矩阵如果P(x1, y1)为错切变换之前的像素点。则错切变换以后相应的像素

P’(x2, y2)当X方向错切变换时:

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当Y方向错切变换时:

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二:程序实现基本思路

实现图像错切变换时,必须考虑图像将目标像素点坐标变为源相点坐标时小数部分对

像素值的影响,这里通过临近点插值算法实现了目标像素值的计算。依据目标像素计

算源像素的公式能够依据上面的数学公式运算以后分别求的x1,y1的值。因为错切以

后图像会在宽或者高上比原图像大,多出来的这些背景像素默认填充颜色为黑色。

类ShearFilter实现了图像水平或者垂直方向的错切变换,支持角度与背景颜色參数

设置。

 三:编程关键点解析

?  计算错切以后图像的宽与高

        double angleValue = (angle/180.0d) * Math.PI;
        outh = vertical ? (int)(height + width * Math.tan(angleValue)) : height;
        outw = vertical ? width : (int)(width + height * Math.tan(angleValue));
        System.out.println("after shear, new width : " + outw);
        System.out.println("after shear, new height: " + outh);
?  依据目标像素点坐标计算源像素点坐标

	double prow = vertical ? row + Math.tan(angleValue) * (col - width) : row;
	double pcol = vertical ?

col : col + Math.tan(angleValue) * (row - height); int[] rgb = getPixel(inPixels, width, height, prow, pcol);

?  临近点插值计算目标像素点像素值

private int[] getPixel(int[] input, int width, int height, 
		double prow, double pcol) {
	double row = Math.floor(prow);
	double col = Math.floor(pcol);
	if(row < 0 || row >= height) {
		return new int[]{backgroundColor.getRed(), 
				backgroundColor.getGreen(), 
				backgroundColor.getBlue()};
	}
	if(col < 0 || col >= width) {
		return new int[]{backgroundColor.getRed(), 
				backgroundColor.getGreen(), 
				backgroundColor.getBlue()};
	}
	double u = vertical ? (prow - row) : pcol - col;
	int nextCol = (int)(col + 1);
	int nextRow = (int)(row + 1);
	if((col + 1) >= width) {
		nextCol = (int)col;
	}
	if((row + 1) >= height) {
		nextRow = (int)row;
	}
	int index1 = (int)(row * width + col);
	int index2 = vertical ? (int)(nextRow * width + col) : (int)(row * width + nextCol);
	
	int tr1, tr2;
	int tg1, tg2;
	int tb1, tb2;
	
    tr1 = (input[index1] >> 16) & 0xff;
    tg1 = (input[index1] >> 8) & 0xff;
    tb1 = input[index1] & 0xff;
    
    tr2 = (input[index2] >> 16) & 0xff;
    tg2 = (input[index2] >> 8) & 0xff;
    tb2 = input[index2] & 0xff;
    
    int tr = (int)(tr1 * (1-u) + tr2 * u);
    int tg = (int)(tg1 * (1-u) + tg2 * u);
    int tb = (int)(tb1 * (1-u) + tb2 * u);
    
	return new int[]{tr, tg, tb};
}
四:执行效果

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五:类ShearFilter完整代码

package com.gloomyfish.filter.study;

import java.awt.Color;
import java.awt.image.BufferedImage;
import java.awt.image.ColorModel;

public class ShearFilter extends AbstractBufferedImageOp {
	private int outw;
	private int outh;
	private double angle;
	private Color backgroundColor;
	private boolean vertical;
	
	public void setVertical(boolean vertical) {
		this.vertical = vertical;
	}

	public ShearFilter()
	{
		backgroundColor = Color.BLACK;
		vertical = false;
		this.angle = 20;
	}
	
	public int getOutw() {
		return outw;
	}
	public void setOutw(int outw) {
		this.outw = outw;
	}
	public int getOuth() {
		return outh;
	}
	public void setOuth(int outh) {
		this.outh = outh;
	}
	public double getAngle() {
		return angle;
	}
	public void setAngle(double angle) {
		this.angle = angle;
	}
	public Color getBackgroundColor() {
		return backgroundColor;
	}
	public void setBackgroundColor(Color backgroundColor) {
		this.backgroundColor = backgroundColor;
	}
	@Override
	public BufferedImage filter(BufferedImage src, BufferedImage dest) {
		int width = src.getWidth();
        int height = src.getHeight();

        double angleValue = (angle/180.0d) * Math.PI;
        outh = vertical ? (int)(height + width * Math.tan(angleValue)) : height;
        outw = vertical ? width : (int)(width + height * Math.tan(angleValue));
        System.out.println("after shear, new width : " + outw);
        System.out.println("after shear, new height: " + outh);
        
        int[] inPixels = new int[width*height];
        int[] outPixels = new int[outh*outw];
        getRGB( src, 0, 0, width, height, inPixels );
        int index = 0;
        for(int row=0; row<outh; row++) {
        	int ta = 0;
        	for(int col=0; col<outw; col++) {
				double prow = vertical ? row + Math.tan(angleValue) * (col - width) : row;
				double pcol = vertical ?

col : col + Math.tan(angleValue) * (row - height); int[] rgb = getPixel(inPixels, width, height, prow, pcol); index = row * outw + col; outPixels[index] = (ta << 24) | (rgb[0] << 16) | (rgb[1] << 8) | rgb[2]; } } if ( dest == null ) dest = createCompatibleDestImage( src, null ); setRGB( dest, 0, 0, outw, outh, outPixels ); return dest; } private int[] getPixel(int[] input, int width, int height, double prow, double pcol) { double row = Math.floor(prow); double col = Math.floor(pcol); if(row < 0 || row >= height) { return new int[]{backgroundColor.getRed(), backgroundColor.getGreen(), backgroundColor.getBlue()}; } if(col < 0 || col >= width) { return new int[]{backgroundColor.getRed(), backgroundColor.getGreen(), backgroundColor.getBlue()}; } double u = vertical ? (prow - row) : pcol - col; int nextCol = (int)(col + 1); int nextRow = (int)(row + 1); if((col + 1) >= width) { nextCol = (int)col; } if((row + 1) >= height) { nextRow = (int)row; } int index1 = (int)(row * width + col); int index2 = vertical ? (int)(nextRow * width + col) : (int)(row * width + nextCol); int tr1, tr2; int tg1, tg2; int tb1, tb2; tr1 = (input[index1] >> 16) & 0xff; tg1 = (input[index1] >> 8) & 0xff; tb1 = input[index1] & 0xff; tr2 = (input[index2] >> 16) & 0xff; tg2 = (input[index2] >> 8) & 0xff; tb2 = input[index2] & 0xff; int tr = (int)(tr1 * (1-u) + tr2 * u); int tg = (int)(tg1 * (1-u) + tg2 * u); int tb = (int)(tb1 * (1-u) + tb2 * u); return new int[]{tr, tg, tb}; } public BufferedImage createCompatibleDestImage(BufferedImage src, ColorModel dstCM) { if ( dstCM == null ) dstCM = src.getColorModel(); return new BufferedImage(dstCM, dstCM.createCompatibleWritableRaster(outw, outh), dstCM.isAlphaPremultiplied(), null); } }

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图像处理之错切变换

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原文地址:http://www.cnblogs.com/mengfanrong/p/5092977.html

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