/*
** Copyright 2005 Huxtable.com. All rights reserved.
*/
package filter;
import java.awt.*;
import java.awt.image.*;
import java.awt.geom.*;
/**
* A filter which applies a convolution kernel to an image.
* @author Jerry Huxtable
*/
public class ConvolveFilter extends AbstractBufferedImageOp {
static final long serialVersionUID = 2239251672685254626L;
public static int ZERO_EDGES = 0;
public static int CLAMP_EDGES = 1;
public static int WRAP_EDGES = 2;
protected Kernel kernel = null;
public boolean alpha = true;
private int edgeAction = CLAMP_EDGES;
/**
* Construct a filter with a null kernel. This is only useful if you're going to change the kernel later on.
*/
public ConvolveFilter() {
this(new float[9]);
}
/**
* Construct a filter with the given 3x3 kernel.
* @param matrix an array of 9 floats containing the kernel
*/
public ConvolveFilter(float[] matrix) {
this(new Kernel(3, 3, matrix));
}
/**
* Construct a filter with the given kernel.
* @param rows the number of rows in the kernel
* @param cols the number of columns in the kernel
* @param matrix an array of rows*cols floats containing the kernel
*/
public ConvolveFilter(int rows, int cols, float[] matrix) {
this(new Kernel(cols, rows, matrix));
}
/**
* Construct a filter with the given 3x3 kernel.
* @param matrix an array of 9 floats containing the kernel
*/
public ConvolveFilter(Kernel kernel) {
this.kernel = kernel;
}
public void setKernel(Kernel kernel) {
this.kernel = kernel;
}
public Kernel getKernel() {
return kernel;
}
public void setEdgeAction(int edgeAction) {
this.edgeAction = edgeAction;
}
public int getEdgeAction() {
return edgeAction;
}
public BufferedImage filter( BufferedImage src, BufferedImage dst ) {
int width = src.getWidth();
int height = src.getHeight();
if ( dst == null )
dst = createCompatibleDestImage( src, null );
int[] inPixels = new int[width*height];
int[] outPixels = new int[width*height];
getRGB( src, 0, 0, width, height, inPixels );
convolve(kernel, inPixels, outPixels, width, height, alpha, edgeAction);
setRGB( dst, 0, 0, width, height, outPixels );
return dst;
}
public BufferedImage createCompatibleDestImage(BufferedImage src, ColorModel dstCM) {
if ( dstCM == null )
dstCM = src.getColorModel();
return new BufferedImage(dstCM, dstCM.createCompatibleWritableRaster(src.getWidth(), src.getHeight()), dstCM.isAlphaPremultiplied(), null);
}
public Rectangle2D getBounds2D( BufferedImage src ) {
return new Rectangle(0, 0, src.getWidth(), src.getHeight());
}
public Point2D getPoint2D( Point2D srcPt, Point2D dstPt ) {
if ( dstPt == null )
dstPt = new Point2D.Double();
dstPt.setLocation( srcPt.getX(), srcPt.getY() );
return dstPt;
}
public RenderingHints getRenderingHints() {
return null;
}
public static void convolve(Kernel kernel, int[] inPixels, int[] outPixels, int width, int height, int edgeAction) {
convolve(kernel, inPixels, outPixels, width, height, true, edgeAction);
}
public static void convolve(Kernel kernel, int[] inPixels, int[] outPixels, int width, int height, boolean alpha, int edgeAction) {
if (kernel.getHeight() == 1)
convolveH(kernel, inPixels, outPixels, width, height, alpha, edgeAction);
else if (kernel.getWidth() == 1)
convolveV(kernel, inPixels, outPixels, width, height, alpha, edgeAction);
else
convolveHV(kernel, inPixels, outPixels, width, height, alpha, edgeAction);
}
/**
* Convolve with a 2D kernel
*/
public static void convolveHV(Kernel kernel, int[] inPixels, int[] outPixels, int width, int height, boolean alpha, int edgeAction) {
int index = 0;
float[] matrix = kernel.getKernelData( null );
int rows = kernel.getHeight();
int cols = kernel.getWidth();
int rows2 = rows/2;
int cols2 = cols/2;
for (int y = 0; y < height; y++) {
for (int x = 0; x < width; x++) {
float r = 0, g = 0, b = 0, a = 0;
for (int row = -rows2; row <= rows2; row++) {
int iy = y+row;
int ioffset;
if (0 <= iy && iy < height)
ioffset = iy*width;
else if ( edgeAction == CLAMP_EDGES )
ioffset = y*width;
else if ( edgeAction == WRAP_EDGES )
ioffset = ((iy+height) % height) * width;
else
continue;
int moffset = cols*(row+rows2)+cols2;
for (int col = -cols2; col <= cols2; col++) {
float f = matrix[moffset+col];
if (f != 0) {
int ix = x+col;
if (!(0 <= ix && ix < width)) {
if ( edgeAction == CLAMP_EDGES )
ix = x;
else if ( edgeAction == WRAP_EDGES )
ix = (x+width) % width;
else
continue;
}
int rgb = inPixels[ioffset+ix];
a += f * ((rgb >> 24) & 0xff);
r += f * ((rgb >> 16) & 0xff);
g += f * ((rgb >> 8) & 0xff);
b += f * (rgb & 0xff);
}
}
}
int ia = alpha ? PixelUtils.clamp((int)(a+0.5)) : 0xff;
int ir = PixelUtils.clamp((int)(r+0.5));
int ig = PixelUtils.clamp((int)(g+0.5));
int ib = PixelUtils.clamp((int)(b+0.5));
outPixels[index++] = (ia << 24) | (ir << 16) | (ig << 8) | ib;
}
}
}
/**
* Convolve with a kernel consisting of one row
*/
public static void convolveH(Kernel kernel, int[] inPixels, int[] outPixels, int width, int height, boolean alpha, int edgeAction) {
int index = 0;
float[] matrix = kernel.getKernelData( null );
int cols = kernel.getWidth();
int cols2 = cols/2;
for (int y = 0; y < height; y++) {
int ioffset = y*width;
for (int x = 0; x < width; x++) {
float r = 0, g = 0, b = 0, a = 0;
int moffset = cols2;
for (int col = -cols2; col <= cols2; col++) {
float f = matrix[moffset+col];
if (f != 0) {
int ix = x+col;
if ( ix < 0 ) {
if ( edgeAction == CLAMP_EDGES )
ix = 0;
else if ( edgeAction == WRAP_EDGES )
ix = (x+width) % width;
} else if ( ix >= width) {
if ( edgeAction == CLAMP_EDGES )
ix = width-1;
else if ( edgeAction == WRAP_EDGES )
ix = (x+width) % width;
}
int rgb = inPixels[ioffset+ix];
a += f * ((rgb >> 24) & 0xff);
r += f * ((rgb >> 16) & 0xff);
g += f * ((rgb >> 8) & 0xff);
b += f * (rgb & 0xff);
}
}
int ia = alpha ? PixelUtils.clamp((int)(a+0.5)) : 0xff;
int ir = PixelUtils.clamp((int)(r+0.5));
int ig = PixelUtils.clamp((int)(g+0.5));
int ib = PixelUtils.clamp((int)(b+0.5));
outPixels[index++] = (ia << 24) | (ir << 16) | (ig << 8) | ib;
}
}
}
/**
* Convolve with a kernel consisting of one column
*/
public static void convolveV(Kernel kernel, int[] inPixels, int[] outPixels, int width, int height, boolean alpha, int edgeAction) {
int index = 0;
float[] matrix = kernel.getKernelData( null );
int rows = kernel.getHeight();
int rows2 = rows/2;
for (int y = 0; y < height; y++) {
for (int x = 0; x < width; x++) {
float r = 0, g = 0, b = 0, a = 0;
for (int row = -rows2; row <= rows2; row++) {
int iy = y+row;
int ioffset;
if ( iy < 0 ) {
if ( edgeAction == CLAMP_EDGES )
ioffset = 0;
else if ( edgeAction == WRAP_EDGES )
ioffset = ((y+height) % height)*width;
else
ioffset = iy*width;
} else if ( iy >= height) {
if ( edgeAction == CLAMP_EDGES )
ioffset = (height-1)*width;
else if ( edgeAction == WRAP_EDGES )
ioffset = ((y+height) % height)*width;
else
ioffset = iy*width;
} else
ioffset = iy*width;
float f = matrix[row+rows2];
if (f != 0) {
int rgb = inPixels[ioffset+x];
a += f * ((rgb >> 24) & 0xff);
r += f * ((rgb >> 16) & 0xff);
g += f * ((rgb >> 8) & 0xff);
b += f * (rgb & 0xff);
}
}
int ia = alpha ? PixelUtils.clamp((int)(a+0.5)) : 0xff;
int ir = PixelUtils.clamp((int)(r+0.5));
int ig = PixelUtils.clamp((int)(g+0.5));
int ib = PixelUtils.clamp((int)(b+0.5));
outPixels[index++] = (ia << 24) | (ir << 16) | (ig << 8) | ib;
}
}
}
public String toString() {
return "Blur/Convolve...";
}
}
最近下载更多
最近浏览更多
