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224 lines (181 loc) · 7.08 KB
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// http://blog.ivank.net/fastest-gaussian-blur.html
package clojure2d.java.filter;
import clojure2d.java.Pixels;
import net.jafama.FastMath;
public final class Blur {
private static void internalProcessH(final int[] scl, int[] tcl, int w, int h, int r) {
double iarr = 1.0 / (r + r + 1);
for(int i=0; i<h; i++) {
int ti = i*w;
int li = ti;
int ri = ti+r;
int fv = scl[ti];
int lv = scl[ti+w-1];
int val = (r+1)*fv;
for(int j=0; j<r; j++) val += scl[ti+j];
for(int j=0; j<=r; j++) {
val += scl[ri++] - fv;
tcl[ti++] = (int)(val*iarr);
}
for(int j=r+1; j<w-r; j++) {
val += scl[ri++] - scl[li++];
tcl[ti++] = (int)(val*iarr);
}
for(int j=w-r; j<w; j++) {
val += lv - scl[li++];
tcl[ti++] = (int)(val*iarr);
}
}
}
private static void internalProcessV(final int[] scl, int[] tcl, int w, int h, int r) {
double iarr = 1.0 / (r + r + 1);
for(int i=0; i<w; i++) {
int ti = i;
int li = ti;
int ri = ti+r*w;
int fv = scl[ti];
int lv = scl[ti+w*(h-1)];
int val = (r+1)*fv;
for(int j=0; j<r; j++) val += scl[ti+j*w];
for(int j=0; j<=r; j++) {
val += scl[ri] - fv;
tcl[ti] = (int)(val*iarr);
ri+=w;
ti+=w;
}
for(int j=r+1; j<h-r; j++) {
val += scl[ri] - scl[li];
tcl[ti] = (int)(val*iarr);
li+=w;
ri+=w;
ti+=w;
}
for(int j=h-r; j<h; j++) {
val += lv - scl[li];
tcl[ti] = (int)(val*iarr);
li+=w;
ti+=w;
}
}
}
public static void horizontalBlur(final int[] in, int[] out, int ch, int w, int h, int r) {
int[] channel = Pixels.getChannel(in, ch);
int[] target = new int[channel.length];
internalProcessH(channel, target, w, h, r);
Pixels.setChannel(out, ch, target);
}
public static void verticalBlur(final int[] in, int[] out, int ch, int w, int h, int r) {
int[] channel = Pixels.getChannel(in, ch);
int[] target = new int[channel.length];
internalProcessV(channel, target, w, h, r);
Pixels.setChannel(out, ch, target);
}
public static void boxBlur(final int[] in, int[] out, int ch, int w, int h, int r) {
int[] channel = Pixels.getChannel(in, ch);
int[] target = new int[channel.length];
internalProcessH(channel, target, w, h, r);
internalProcessV(target, channel, w, h, r);
Pixels.setChannel(out, ch, channel);
}
//
private static int[] boxesForGauss(double sigma, int n) {
double wIdeal = FastMath.sqrt((12.0*sigma*sigma/n)+1.0);
int wl = (int)FastMath.floor(wIdeal);
if( (wl & 1) == 0) { wl--; }
int wu = wl+2;
double mIdeal = (12.0*sigma*sigma - n*wl*wl - ((n*wl)<<2) - 3.0*n)/(-4*wl - 4);
int m = (int)FastMath.round(mIdeal);
int[] sizes = new int[n];
for(int i=0; i<n; i++) sizes[i] = i<m?wl:wu;
return sizes;
}
public static void gaussianBlur(final int[] in, int[] out, int ch, int w, int h, int r) {
int[] channel = Pixels.getChannel(in, ch);
int[] target = new int[channel.length];
int[] bxs = boxesForGauss(r,3);
internalProcessH(channel, target, w, h, (bxs[0]-1)/2);
internalProcessV(target, channel, w, h, (bxs[0]-1)/2);
internalProcessH(channel, target, w, h, (bxs[1]-1)/2);
internalProcessV(target, channel, w, h, (bxs[1]-1)/2);
internalProcessH(channel, target, w, h, (bxs[2]-1)/2);
internalProcessV(target, channel, w, h, (bxs[2]-1)/2);
Pixels.setChannel(out, ch, channel);
}
// double part
private static void internalProcessH(final double[] scl, double[] tcl, int w, int h, int r) {
double iarr = 1.0 / (r + r + 1);
for(int i=0; i<h; i++) {
int ti = i*w;
int li = ti;
int ri = ti+r;
double fv = scl[ti];
double lv = scl[ti+w-1];
double val = (r+1)*fv;
for(int j=0; j<r; j++) val += scl[ti+j];
for(int j=0; j<=r; j++) {
val += scl[ri++] - fv;
tcl[ti++] = val*iarr;
}
for(int j=r+1; j<w-r; j++) {
val += scl[ri++] - scl[li++];
tcl[ti++] = val*iarr;
}
for(int j=w-r; j<w; j++) {
val += lv - scl[li++];
tcl[ti++] = val*iarr;
}
}
}
private static void internalProcessV(final double[] scl, double[] tcl, int w, int h, int r) {
double iarr = 1.0 / (r + r + 1);
for(int i=0; i<w; i++) {
int ti = i;
int li = ti;
int ri = ti+r*w;
double fv = scl[ti];
double lv = scl[ti+w*(h-1)];
double val = (r+1)*fv;
for(int j=0; j<r; j++) val += scl[ti+j*w];
for(int j=0; j<=r; j++) {
val += scl[ri] - fv;
tcl[ti] = val*iarr;
ri+=w;
ti+=w;
}
for(int j=r+1; j<h-r; j++) {
val += scl[ri] - scl[li];
tcl[ti] = val*iarr;
li+=w;
ri+=w;
ti+=w;
}
for(int j=h-r; j<h; j++) {
val += lv - scl[li];
tcl[ti] = val*iarr;
li+=w;
ti+=w;
}
}
}
public static void horizontalBlur(final double[] in, double[] out, int w, int h, int r) {
internalProcessH(in, out, w, h, r);
}
public static void verticalBlur(final double[] in, double[] out, int w, int h, int r) {
internalProcessV(in, out, w, h, r);
}
public static void boxBlur(final double[] in, double[] out, int w, int h, int r) {
double[] target = new double[in.length];
internalProcessH(in, target, w, h, r);
internalProcessV(target, out, w, h, r);
}
public static void gaussianBlur(final double[] in, double[] out, int w, int h, int r) {
double[] target = new double[in.length];
int[] bxs = boxesForGauss(r,3);
internalProcessH(in, target, w, h, (bxs[0]-1)/2);
internalProcessV(target, out, w, h, (bxs[0]-1)/2);
internalProcessH(out, target, w, h, (bxs[1]-1)/2);
internalProcessV(target, out, w, h, (bxs[1]-1)/2);
internalProcessH(out, target, w, h, (bxs[2]-1)/2);
internalProcessV(target, out, w, h, (bxs[2]-1)/2);
}
}