boofcv.alg.filter.convolve.noborder.ConvolveImageUnrolled_S32_S32 Maven / Gradle / Ivy
/*
* Copyright (c) 2011-2016, Peter Abeles. All Rights Reserved.
*
* This file is part of BoofCV (http://boofcv.org).
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package boofcv.alg.filter.convolve.noborder;
import boofcv.struct.convolve.Kernel1D_I32;
import boofcv.struct.convolve.Kernel2D_I32;
import boofcv.struct.image.GrayS32;
import javax.annotation.Generated;
/**
*
* Unrolls the convolution kernel to reduce array accessing and save often used variables to the stack.
*
*
*
* Unrolling the image being convolved resulting in an additional 10% performance boost on a Core i7 processor,
* see commented out code below. Due to the added complexity it was decided that this performance boost was
* not worth it. By comparison, unrolling the kernel causes a performance boost between 2 and 3 times.
*
*
*
* DO NOT MODIFY. This class was automatically generated by GenerateConvolvedUnrolled.
*
*
* @author Peter Abeles
*/
@Generated({"boofcv.alg.filter.convolve.noborder.GenerateConvolvedUnrolled"})
public class ConvolveImageUnrolled_S32_S32 {
public static boolean horizontal( Kernel1D_I32 kernel ,
GrayS32 image, GrayS32 dest) {
// Unrolled functions only exist for symmetric kernels with an odd width
if( kernel.offset != kernel.width/2 || kernel.width%2 == 0 )
return false;
switch( kernel.width ) {
case 3:
horizontal3(kernel,image,dest);
break;
case 5:
horizontal5(kernel,image,dest);
break;
case 7:
horizontal7(kernel,image,dest);
break;
case 9:
horizontal9(kernel,image,dest);
break;
case 11:
horizontal11(kernel,image,dest);
break;
default:
return false;
}
return true;
}
public static boolean vertical( Kernel1D_I32 kernel ,
GrayS32 image, GrayS32 dest) {
// Unrolled functions only exist for symmetric kernels with an odd width
if( kernel.offset != kernel.width/2 || kernel.width%2 == 0 )
return false;
switch( kernel.width ) {
case 3:
vertical3(kernel,image,dest);
break;
case 5:
vertical5(kernel,image,dest);
break;
case 7:
vertical7(kernel,image,dest);
break;
case 9:
vertical9(kernel,image,dest);
break;
case 11:
vertical11(kernel,image,dest);
break;
default:
return false;
}
return true;
}
public static boolean convolve( Kernel2D_I32 kernel ,
GrayS32 image, GrayS32 dest) {
// Unrolled functions only exist for symmetric kernels with an odd width
if( kernel.offset != kernel.width/2 || kernel.width%2 == 0 )
return false;
switch( kernel.width ) {
case 3:
convolve3(kernel,image,dest);
break;
case 5:
convolve5(kernel,image,dest);
break;
case 7:
convolve7(kernel,image,dest);
break;
case 9:
convolve9(kernel,image,dest);
break;
case 11:
convolve11(kernel,image,dest);
break;
default:
return false;
}
return true;
}
public static void horizontal3( Kernel1D_I32 kernel , GrayS32 image, GrayS32 dest )
{
final int[] dataSrc = image.data;
final int[] dataDst = dest.data;
final int k1 = kernel.data[0];
final int k2 = kernel.data[1];
final int k3 = kernel.data[2];
final int radius = kernel.getRadius();
final int width = image.getWidth();
for( int i = 0; i < image.height; i++ ) {
int indexDst = dest.startIndex + i*dest.stride+radius;
int j = image.startIndex + i*image.stride - radius;
final int jEnd = j+width-radius;
for( j += radius; j < jEnd; j++ ) {
int indexSrc = j;
int total = (dataSrc[indexSrc++])*k1;
total += (dataSrc[indexSrc++])*k2;
total += (dataSrc[indexSrc])*k3;
dataDst[indexDst++] = total;
}
}
}
public static void horizontal5( Kernel1D_I32 kernel , GrayS32 image, GrayS32 dest )
{
final int[] dataSrc = image.data;
final int[] dataDst = dest.data;
final int k1 = kernel.data[0];
final int k2 = kernel.data[1];
final int k3 = kernel.data[2];
final int k4 = kernel.data[3];
final int k5 = kernel.data[4];
final int radius = kernel.getRadius();
final int width = image.getWidth();
for( int i = 0; i < image.height; i++ ) {
int indexDst = dest.startIndex + i*dest.stride+radius;
int j = image.startIndex + i*image.stride - radius;
final int jEnd = j+width-radius;
for( j += radius; j < jEnd; j++ ) {
int indexSrc = j;
int total = (dataSrc[indexSrc++])*k1;
total += (dataSrc[indexSrc++])*k2;
total += (dataSrc[indexSrc++])*k3;
total += (dataSrc[indexSrc++])*k4;
total += (dataSrc[indexSrc])*k5;
dataDst[indexDst++] = total;
}
}
}
public static void horizontal7( Kernel1D_I32 kernel , GrayS32 image, GrayS32 dest )
{
final int[] dataSrc = image.data;
final int[] dataDst = dest.data;
final int k1 = kernel.data[0];
final int k2 = kernel.data[1];
final int k3 = kernel.data[2];
final int k4 = kernel.data[3];
final int k5 = kernel.data[4];
final int k6 = kernel.data[5];
final int k7 = kernel.data[6];
final int radius = kernel.getRadius();
final int width = image.getWidth();
for( int i = 0; i < image.height; i++ ) {
int indexDst = dest.startIndex + i*dest.stride+radius;
int j = image.startIndex + i*image.stride - radius;
final int jEnd = j+width-radius;
for( j += radius; j < jEnd; j++ ) {
int indexSrc = j;
int total = (dataSrc[indexSrc++])*k1;
total += (dataSrc[indexSrc++])*k2;
total += (dataSrc[indexSrc++])*k3;
total += (dataSrc[indexSrc++])*k4;
total += (dataSrc[indexSrc++])*k5;
total += (dataSrc[indexSrc++])*k6;
total += (dataSrc[indexSrc])*k7;
dataDst[indexDst++] = total;
}
}
}
public static void horizontal9( Kernel1D_I32 kernel , GrayS32 image, GrayS32 dest )
{
final int[] dataSrc = image.data;
final int[] dataDst = dest.data;
final int k1 = kernel.data[0];
final int k2 = kernel.data[1];
final int k3 = kernel.data[2];
final int k4 = kernel.data[3];
final int k5 = kernel.data[4];
final int k6 = kernel.data[5];
final int k7 = kernel.data[6];
final int k8 = kernel.data[7];
final int k9 = kernel.data[8];
final int radius = kernel.getRadius();
final int width = image.getWidth();
for( int i = 0; i < image.height; i++ ) {
int indexDst = dest.startIndex + i*dest.stride+radius;
int j = image.startIndex + i*image.stride - radius;
final int jEnd = j+width-radius;
for( j += radius; j < jEnd; j++ ) {
int indexSrc = j;
int total = (dataSrc[indexSrc++])*k1;
total += (dataSrc[indexSrc++])*k2;
total += (dataSrc[indexSrc++])*k3;
total += (dataSrc[indexSrc++])*k4;
total += (dataSrc[indexSrc++])*k5;
total += (dataSrc[indexSrc++])*k6;
total += (dataSrc[indexSrc++])*k7;
total += (dataSrc[indexSrc++])*k8;
total += (dataSrc[indexSrc])*k9;
dataDst[indexDst++] = total;
}
}
}
public static void horizontal11( Kernel1D_I32 kernel , GrayS32 image, GrayS32 dest )
{
final int[] dataSrc = image.data;
final int[] dataDst = dest.data;
final int k1 = kernel.data[0];
final int k2 = kernel.data[1];
final int k3 = kernel.data[2];
final int k4 = kernel.data[3];
final int k5 = kernel.data[4];
final int k6 = kernel.data[5];
final int k7 = kernel.data[6];
final int k8 = kernel.data[7];
final int k9 = kernel.data[8];
final int k10 = kernel.data[9];
final int k11 = kernel.data[10];
final int radius = kernel.getRadius();
final int width = image.getWidth();
for( int i = 0; i < image.height; i++ ) {
int indexDst = dest.startIndex + i*dest.stride+radius;
int j = image.startIndex + i*image.stride - radius;
final int jEnd = j+width-radius;
for( j += radius; j < jEnd; j++ ) {
int indexSrc = j;
int total = (dataSrc[indexSrc++])*k1;
total += (dataSrc[indexSrc++])*k2;
total += (dataSrc[indexSrc++])*k3;
total += (dataSrc[indexSrc++])*k4;
total += (dataSrc[indexSrc++])*k5;
total += (dataSrc[indexSrc++])*k6;
total += (dataSrc[indexSrc++])*k7;
total += (dataSrc[indexSrc++])*k8;
total += (dataSrc[indexSrc++])*k9;
total += (dataSrc[indexSrc++])*k10;
total += (dataSrc[indexSrc])*k11;
dataDst[indexDst++] = total;
}
}
}
public static void vertical3( Kernel1D_I32 kernel , GrayS32 image, GrayS32 dest )
{
final int[] dataSrc = image.data;
final int[] dataDst = dest.data;
final int k1 = kernel.data[0];
final int k2 = kernel.data[1];
final int k3 = kernel.data[2];
final int radius = kernel.getRadius();
final int imgWidth = dest.getWidth();
final int imgHeight = dest.getHeight();
final int yEnd = imgHeight-radius;
for( int y = radius; y < yEnd; y++ ) {
int indexDst = dest.startIndex+y*dest.stride;
int i = image.startIndex + (y-radius)*image.stride;
final int iEnd = i+imgWidth;
for( ; i < iEnd; i++ ) {
int indexSrc = i;
int total = (dataSrc[indexSrc]) * k1;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k2;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k3;
dataDst[indexDst++] = total;
}
}
}
public static void vertical5( Kernel1D_I32 kernel , GrayS32 image, GrayS32 dest )
{
final int[] dataSrc = image.data;
final int[] dataDst = dest.data;
final int k1 = kernel.data[0];
final int k2 = kernel.data[1];
final int k3 = kernel.data[2];
final int k4 = kernel.data[3];
final int k5 = kernel.data[4];
final int radius = kernel.getRadius();
final int imgWidth = dest.getWidth();
final int imgHeight = dest.getHeight();
final int yEnd = imgHeight-radius;
for( int y = radius; y < yEnd; y++ ) {
int indexDst = dest.startIndex+y*dest.stride;
int i = image.startIndex + (y-radius)*image.stride;
final int iEnd = i+imgWidth;
for( ; i < iEnd; i++ ) {
int indexSrc = i;
int total = (dataSrc[indexSrc]) * k1;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k2;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k3;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k4;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k5;
dataDst[indexDst++] = total;
}
}
}
public static void vertical7( Kernel1D_I32 kernel , GrayS32 image, GrayS32 dest )
{
final int[] dataSrc = image.data;
final int[] dataDst = dest.data;
final int k1 = kernel.data[0];
final int k2 = kernel.data[1];
final int k3 = kernel.data[2];
final int k4 = kernel.data[3];
final int k5 = kernel.data[4];
final int k6 = kernel.data[5];
final int k7 = kernel.data[6];
final int radius = kernel.getRadius();
final int imgWidth = dest.getWidth();
final int imgHeight = dest.getHeight();
final int yEnd = imgHeight-radius;
for( int y = radius; y < yEnd; y++ ) {
int indexDst = dest.startIndex+y*dest.stride;
int i = image.startIndex + (y-radius)*image.stride;
final int iEnd = i+imgWidth;
for( ; i < iEnd; i++ ) {
int indexSrc = i;
int total = (dataSrc[indexSrc]) * k1;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k2;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k3;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k4;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k5;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k6;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k7;
dataDst[indexDst++] = total;
}
}
}
public static void vertical9( Kernel1D_I32 kernel , GrayS32 image, GrayS32 dest )
{
final int[] dataSrc = image.data;
final int[] dataDst = dest.data;
final int k1 = kernel.data[0];
final int k2 = kernel.data[1];
final int k3 = kernel.data[2];
final int k4 = kernel.data[3];
final int k5 = kernel.data[4];
final int k6 = kernel.data[5];
final int k7 = kernel.data[6];
final int k8 = kernel.data[7];
final int k9 = kernel.data[8];
final int radius = kernel.getRadius();
final int imgWidth = dest.getWidth();
final int imgHeight = dest.getHeight();
final int yEnd = imgHeight-radius;
for( int y = radius; y < yEnd; y++ ) {
int indexDst = dest.startIndex+y*dest.stride;
int i = image.startIndex + (y-radius)*image.stride;
final int iEnd = i+imgWidth;
for( ; i < iEnd; i++ ) {
int indexSrc = i;
int total = (dataSrc[indexSrc]) * k1;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k2;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k3;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k4;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k5;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k6;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k7;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k8;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k9;
dataDst[indexDst++] = total;
}
}
}
public static void vertical11( Kernel1D_I32 kernel , GrayS32 image, GrayS32 dest )
{
final int[] dataSrc = image.data;
final int[] dataDst = dest.data;
final int k1 = kernel.data[0];
final int k2 = kernel.data[1];
final int k3 = kernel.data[2];
final int k4 = kernel.data[3];
final int k5 = kernel.data[4];
final int k6 = kernel.data[5];
final int k7 = kernel.data[6];
final int k8 = kernel.data[7];
final int k9 = kernel.data[8];
final int k10 = kernel.data[9];
final int k11 = kernel.data[10];
final int radius = kernel.getRadius();
final int imgWidth = dest.getWidth();
final int imgHeight = dest.getHeight();
final int yEnd = imgHeight-radius;
for( int y = radius; y < yEnd; y++ ) {
int indexDst = dest.startIndex+y*dest.stride;
int i = image.startIndex + (y-radius)*image.stride;
final int iEnd = i+imgWidth;
for( ; i < iEnd; i++ ) {
int indexSrc = i;
int total = (dataSrc[indexSrc]) * k1;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k2;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k3;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k4;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k5;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k6;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k7;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k8;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k9;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k10;
indexSrc += image.stride;
total += (dataSrc[indexSrc])*k11;
dataDst[indexDst++] = total;
}
}
}
public static void convolve3( Kernel2D_I32 kernel, GrayS32 src, GrayS32 dest)
{
final int[] dataSrc = src.data;
final int[] dataDst = dest.data;
final int width = src.getWidth();
final int height = src.getHeight();
final int kernelRadius = kernel.getRadius();
for( int y = kernelRadius; y < height-kernelRadius; y++ ) {
// first time through the value needs to be set
int k1 = kernel.data[0];
int k2 = kernel.data[1];
int k3 = kernel.data[2];
int indexDst = dest.startIndex + y*dest.stride+kernelRadius;
int indexSrcRow = src.startIndex+(y-kernelRadius)*src.stride-kernelRadius;
for( int x = kernelRadius; x < width-kernelRadius; x++ ) {
int indexSrc = indexSrcRow + x;
int total = 0;
total += (dataSrc[indexSrc++] )* k1;
total += (dataSrc[indexSrc++] )* k2;
total += (dataSrc[indexSrc] )* k3;
dataDst[indexDst++] = total;
}
// rest of the convolution rows are an addition
for( int i = 1; i < 3; i++ ) {
indexDst = dest.startIndex + y*dest.stride+kernelRadius;
indexSrcRow = src.startIndex+(y+i-kernelRadius)*src.stride-kernelRadius;
k1 = kernel.data[i*3 + 0];
k2 = kernel.data[i*3 + 1];
k3 = kernel.data[i*3 + 2];
for( int x = kernelRadius; x < width-kernelRadius; x++ ) {
int indexSrc = indexSrcRow+x;
int total = 0;
total += (dataSrc[indexSrc++] )* k1;
total += (dataSrc[indexSrc++] )* k2;
total += (dataSrc[indexSrc] )* k3;
dataDst[indexDst++] += total;
}
}
}
}
public static void convolve5( Kernel2D_I32 kernel, GrayS32 src, GrayS32 dest)
{
final int[] dataSrc = src.data;
final int[] dataDst = dest.data;
final int width = src.getWidth();
final int height = src.getHeight();
final int kernelRadius = kernel.getRadius();
for( int y = kernelRadius; y < height-kernelRadius; y++ ) {
// first time through the value needs to be set
int k1 = kernel.data[0];
int k2 = kernel.data[1];
int k3 = kernel.data[2];
int k4 = kernel.data[3];
int k5 = kernel.data[4];
int indexDst = dest.startIndex + y*dest.stride+kernelRadius;
int indexSrcRow = src.startIndex+(y-kernelRadius)*src.stride-kernelRadius;
for( int x = kernelRadius; x < width-kernelRadius; x++ ) {
int indexSrc = indexSrcRow + x;
int total = 0;
total += (dataSrc[indexSrc++] )* k1;
total += (dataSrc[indexSrc++] )* k2;
total += (dataSrc[indexSrc++] )* k3;
total += (dataSrc[indexSrc++] )* k4;
total += (dataSrc[indexSrc] )* k5;
dataDst[indexDst++] = total;
}
// rest of the convolution rows are an addition
for( int i = 1; i < 5; i++ ) {
indexDst = dest.startIndex + y*dest.stride+kernelRadius;
indexSrcRow = src.startIndex+(y+i-kernelRadius)*src.stride-kernelRadius;
k1 = kernel.data[i*5 + 0];
k2 = kernel.data[i*5 + 1];
k3 = kernel.data[i*5 + 2];
k4 = kernel.data[i*5 + 3];
k5 = kernel.data[i*5 + 4];
for( int x = kernelRadius; x < width-kernelRadius; x++ ) {
int indexSrc = indexSrcRow+x;
int total = 0;
total += (dataSrc[indexSrc++] )* k1;
total += (dataSrc[indexSrc++] )* k2;
total += (dataSrc[indexSrc++] )* k3;
total += (dataSrc[indexSrc++] )* k4;
total += (dataSrc[indexSrc] )* k5;
dataDst[indexDst++] += total;
}
}
}
}
public static void convolve7( Kernel2D_I32 kernel, GrayS32 src, GrayS32 dest)
{
final int[] dataSrc = src.data;
final int[] dataDst = dest.data;
final int width = src.getWidth();
final int height = src.getHeight();
final int kernelRadius = kernel.getRadius();
for( int y = kernelRadius; y < height-kernelRadius; y++ ) {
// first time through the value needs to be set
int k1 = kernel.data[0];
int k2 = kernel.data[1];
int k3 = kernel.data[2];
int k4 = kernel.data[3];
int k5 = kernel.data[4];
int k6 = kernel.data[5];
int k7 = kernel.data[6];
int indexDst = dest.startIndex + y*dest.stride+kernelRadius;
int indexSrcRow = src.startIndex+(y-kernelRadius)*src.stride-kernelRadius;
for( int x = kernelRadius; x < width-kernelRadius; x++ ) {
int indexSrc = indexSrcRow + x;
int total = 0;
total += (dataSrc[indexSrc++] )* k1;
total += (dataSrc[indexSrc++] )* k2;
total += (dataSrc[indexSrc++] )* k3;
total += (dataSrc[indexSrc++] )* k4;
total += (dataSrc[indexSrc++] )* k5;
total += (dataSrc[indexSrc++] )* k6;
total += (dataSrc[indexSrc] )* k7;
dataDst[indexDst++] = total;
}
// rest of the convolution rows are an addition
for( int i = 1; i < 7; i++ ) {
indexDst = dest.startIndex + y*dest.stride+kernelRadius;
indexSrcRow = src.startIndex+(y+i-kernelRadius)*src.stride-kernelRadius;
k1 = kernel.data[i*7 + 0];
k2 = kernel.data[i*7 + 1];
k3 = kernel.data[i*7 + 2];
k4 = kernel.data[i*7 + 3];
k5 = kernel.data[i*7 + 4];
k6 = kernel.data[i*7 + 5];
k7 = kernel.data[i*7 + 6];
for( int x = kernelRadius; x < width-kernelRadius; x++ ) {
int indexSrc = indexSrcRow+x;
int total = 0;
total += (dataSrc[indexSrc++] )* k1;
total += (dataSrc[indexSrc++] )* k2;
total += (dataSrc[indexSrc++] )* k3;
total += (dataSrc[indexSrc++] )* k4;
total += (dataSrc[indexSrc++] )* k5;
total += (dataSrc[indexSrc++] )* k6;
total += (dataSrc[indexSrc] )* k7;
dataDst[indexDst++] += total;
}
}
}
}
public static void convolve9( Kernel2D_I32 kernel, GrayS32 src, GrayS32 dest)
{
final int[] dataSrc = src.data;
final int[] dataDst = dest.data;
final int width = src.getWidth();
final int height = src.getHeight();
final int kernelRadius = kernel.getRadius();
for( int y = kernelRadius; y < height-kernelRadius; y++ ) {
// first time through the value needs to be set
int k1 = kernel.data[0];
int k2 = kernel.data[1];
int k3 = kernel.data[2];
int k4 = kernel.data[3];
int k5 = kernel.data[4];
int k6 = kernel.data[5];
int k7 = kernel.data[6];
int k8 = kernel.data[7];
int k9 = kernel.data[8];
int indexDst = dest.startIndex + y*dest.stride+kernelRadius;
int indexSrcRow = src.startIndex+(y-kernelRadius)*src.stride-kernelRadius;
for( int x = kernelRadius; x < width-kernelRadius; x++ ) {
int indexSrc = indexSrcRow + x;
int total = 0;
total += (dataSrc[indexSrc++] )* k1;
total += (dataSrc[indexSrc++] )* k2;
total += (dataSrc[indexSrc++] )* k3;
total += (dataSrc[indexSrc++] )* k4;
total += (dataSrc[indexSrc++] )* k5;
total += (dataSrc[indexSrc++] )* k6;
total += (dataSrc[indexSrc++] )* k7;
total += (dataSrc[indexSrc++] )* k8;
total += (dataSrc[indexSrc] )* k9;
dataDst[indexDst++] = total;
}
// rest of the convolution rows are an addition
for( int i = 1; i < 9; i++ ) {
indexDst = dest.startIndex + y*dest.stride+kernelRadius;
indexSrcRow = src.startIndex+(y+i-kernelRadius)*src.stride-kernelRadius;
k1 = kernel.data[i*9 + 0];
k2 = kernel.data[i*9 + 1];
k3 = kernel.data[i*9 + 2];
k4 = kernel.data[i*9 + 3];
k5 = kernel.data[i*9 + 4];
k6 = kernel.data[i*9 + 5];
k7 = kernel.data[i*9 + 6];
k8 = kernel.data[i*9 + 7];
k9 = kernel.data[i*9 + 8];
for( int x = kernelRadius; x < width-kernelRadius; x++ ) {
int indexSrc = indexSrcRow+x;
int total = 0;
total += (dataSrc[indexSrc++] )* k1;
total += (dataSrc[indexSrc++] )* k2;
total += (dataSrc[indexSrc++] )* k3;
total += (dataSrc[indexSrc++] )* k4;
total += (dataSrc[indexSrc++] )* k5;
total += (dataSrc[indexSrc++] )* k6;
total += (dataSrc[indexSrc++] )* k7;
total += (dataSrc[indexSrc++] )* k8;
total += (dataSrc[indexSrc] )* k9;
dataDst[indexDst++] += total;
}
}
}
}
public static void convolve11( Kernel2D_I32 kernel, GrayS32 src, GrayS32 dest)
{
final int[] dataSrc = src.data;
final int[] dataDst = dest.data;
final int width = src.getWidth();
final int height = src.getHeight();
final int kernelRadius = kernel.getRadius();
for( int y = kernelRadius; y < height-kernelRadius; y++ ) {
// first time through the value needs to be set
int k1 = kernel.data[0];
int k2 = kernel.data[1];
int k3 = kernel.data[2];
int k4 = kernel.data[3];
int k5 = kernel.data[4];
int k6 = kernel.data[5];
int k7 = kernel.data[6];
int k8 = kernel.data[7];
int k9 = kernel.data[8];
int k10 = kernel.data[9];
int k11 = kernel.data[10];
int indexDst = dest.startIndex + y*dest.stride+kernelRadius;
int indexSrcRow = src.startIndex+(y-kernelRadius)*src.stride-kernelRadius;
for( int x = kernelRadius; x < width-kernelRadius; x++ ) {
int indexSrc = indexSrcRow + x;
int total = 0;
total += (dataSrc[indexSrc++] )* k1;
total += (dataSrc[indexSrc++] )* k2;
total += (dataSrc[indexSrc++] )* k3;
total += (dataSrc[indexSrc++] )* k4;
total += (dataSrc[indexSrc++] )* k5;
total += (dataSrc[indexSrc++] )* k6;
total += (dataSrc[indexSrc++] )* k7;
total += (dataSrc[indexSrc++] )* k8;
total += (dataSrc[indexSrc++] )* k9;
total += (dataSrc[indexSrc++] )* k10;
total += (dataSrc[indexSrc] )* k11;
dataDst[indexDst++] = total;
}
// rest of the convolution rows are an addition
for( int i = 1; i < 11; i++ ) {
indexDst = dest.startIndex + y*dest.stride+kernelRadius;
indexSrcRow = src.startIndex+(y+i-kernelRadius)*src.stride-kernelRadius;
k1 = kernel.data[i*11 + 0];
k2 = kernel.data[i*11 + 1];
k3 = kernel.data[i*11 + 2];
k4 = kernel.data[i*11 + 3];
k5 = kernel.data[i*11 + 4];
k6 = kernel.data[i*11 + 5];
k7 = kernel.data[i*11 + 6];
k8 = kernel.data[i*11 + 7];
k9 = kernel.data[i*11 + 8];
k10 = kernel.data[i*11 + 9];
k11 = kernel.data[i*11 + 10];
for( int x = kernelRadius; x < width-kernelRadius; x++ ) {
int indexSrc = indexSrcRow+x;
int total = 0;
total += (dataSrc[indexSrc++] )* k1;
total += (dataSrc[indexSrc++] )* k2;
total += (dataSrc[indexSrc++] )* k3;
total += (dataSrc[indexSrc++] )* k4;
total += (dataSrc[indexSrc++] )* k5;
total += (dataSrc[indexSrc++] )* k6;
total += (dataSrc[indexSrc++] )* k7;
total += (dataSrc[indexSrc++] )* k8;
total += (dataSrc[indexSrc++] )* k9;
total += (dataSrc[indexSrc++] )* k10;
total += (dataSrc[indexSrc] )* k11;
dataDst[indexDst++] += total;
}
}
}
}
}