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opencv/modules/imgproc/src/phasecorr.cpp

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/*********************************************************************
* Software License Agreement (BSD License)
*
* Copyright (c) 2008-2011, William Lucas
* All rights reserved.
*
* Redistribution and use in source and binary forms, with or without
* modification, are permitted provided that the following conditions
* are met:
*
* * Redistributions of source code must retain the above copyright
* notice, this list of conditions and the following disclaimer.
* * Redistributions in binary form must reproduce the above
* copyright notice, this list of conditions and the following
* disclaimer in the documentation and/or other materials provided
* with the distribution.
* * Neither the name of the Willow Garage nor the names of its
* contributors may be used to endorse or promote products derived
* from this software without specific prior written permission.
*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
* "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
* LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS
* FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE
* COPYRIGHT OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT,
* INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING,
* BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES;
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* LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN
* ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE
* POSSIBILITY OF SUCH DAMAGE.
*********************************************************************/
#include "precomp.hpp"
#include <vector>
namespace cv
{
static void magSpectrums( InputArray _src, OutputArray _dst)
{
Mat src = _src.getMat();
int depth = src.depth(), cn = src.channels(), type = src.type();
int rows = src.rows, cols = src.cols;
int j, k;
CV_Assert( type == CV_32FC1 || type == CV_32FC2 || type == CV_64FC1 || type == CV_64FC2 );
if(src.depth() == CV_32F)
_dst.create( src.rows, src.cols, CV_32FC1 );
else
_dst.create( src.rows, src.cols, CV_64FC1 );
Mat dst = _dst.getMat();
dst.setTo(0);//Mat elements are not equal to zero by default!
bool is_1d = (rows == 1 || (cols == 1 && src.isContinuous() && dst.isContinuous()));
if( is_1d )
cols = cols + rows - 1, rows = 1;
int ncols = cols*cn;
int j0 = cn == 1;
int j1 = ncols - (cols % 2 == 0 && cn == 1);
if( depth == CV_32F )
{
const float* dataSrc = (const float*)src.data;
float* dataDst = (float*)dst.data;
size_t stepSrc = src.step/sizeof(dataSrc[0]);
size_t stepDst = dst.step/sizeof(dataDst[0]);
if( !is_1d && cn == 1 )
{
for( k = 0; k < (cols % 2 ? 1 : 2); k++ )
{
if( k == 1 )
dataSrc += cols - 1, dataDst += cols - 1;
dataDst[0] = dataSrc[0]*dataSrc[0];
if( rows % 2 == 0 )
dataDst[(rows-1)*stepDst] = dataSrc[(rows-1)*stepSrc]*dataSrc[(rows-1)*stepSrc];
for( j = 1; j <= rows - 2; j += 2 )
{
dataDst[j*stepDst] = (float)std::sqrt((double)dataSrc[j*stepSrc]*dataSrc[j*stepSrc] +
(double)dataSrc[(j+1)*stepSrc]*dataSrc[(j+1)*stepSrc]);
}
if( k == 1 )
dataSrc -= cols - 1, dataDst -= cols - 1;
}
}
for( ; rows--; dataSrc += stepSrc, dataDst += stepDst )
{
if( is_1d && cn == 1 )
{
dataDst[0] = dataSrc[0]*dataSrc[0];
if( cols % 2 == 0 )
dataDst[j1] = dataSrc[j1]*dataSrc[j1];
}
for( j = j0; j < j1; j += 2 )
{
dataDst[j] = (float)std::sqrt((double)dataSrc[j]*dataSrc[j] + (double)dataSrc[j+1]*dataSrc[j+1]);
}
}
}
else
{
const double* dataSrc = (const double*)src.data;
double* dataDst = (double*)dst.data;
size_t stepSrc = src.step/sizeof(dataSrc[0]);
size_t stepDst = dst.step/sizeof(dataDst[0]);
if( !is_1d && cn == 1 )
{
for( k = 0; k < (cols % 2 ? 1 : 2); k++ )
{
if( k == 1 )
dataSrc += cols - 1, dataDst += cols - 1;
dataDst[0] = dataSrc[0]*dataSrc[0];
if( rows % 2 == 0 )
dataDst[(rows-1)*stepDst] = dataSrc[(rows-1)*stepSrc]*dataSrc[(rows-1)*stepSrc];
for( j = 1; j <= rows - 2; j += 2 )
{
dataDst[j*stepDst] = std::sqrt(dataSrc[j*stepSrc]*dataSrc[j*stepSrc] +
dataSrc[(j+1)*stepSrc]*dataSrc[(j+1)*stepSrc]);
}
if( k == 1 )
dataSrc -= cols - 1, dataDst -= cols - 1;
}
}
for( ; rows--; dataSrc += stepSrc, dataDst += stepDst )
{
if( is_1d && cn == 1 )
{
dataDst[0] = dataSrc[0]*dataSrc[0];
if( cols % 2 == 0 )
dataDst[j1] = dataSrc[j1]*dataSrc[j1];
}
for( j = j0; j < j1; j += 2 )
{
dataDst[j] = std::sqrt(dataSrc[j]*dataSrc[j] + dataSrc[j+1]*dataSrc[j+1]);
}
}
}
}
static void divSpectrums( InputArray _srcA, InputArray _srcB, OutputArray _dst, int flags, bool conjB)
{
Mat srcA = _srcA.getMat(), srcB = _srcB.getMat();
int depth = srcA.depth(), cn = srcA.channels(), type = srcA.type();
int rows = srcA.rows, cols = srcA.cols;
int j, k;
CV_Assert( type == srcB.type() && srcA.size() == srcB.size() );
CV_Assert( type == CV_32FC1 || type == CV_32FC2 || type == CV_64FC1 || type == CV_64FC2 );
_dst.create( srcA.rows, srcA.cols, type );
Mat dst = _dst.getMat();
bool is_1d = (flags & DFT_ROWS) || (rows == 1 || (cols == 1 &&
srcA.isContinuous() && srcB.isContinuous() && dst.isContinuous()));
if( is_1d && !(flags & DFT_ROWS) )
cols = cols + rows - 1, rows = 1;
int ncols = cols*cn;
int j0 = cn == 1;
int j1 = ncols - (cols % 2 == 0 && cn == 1);
if( depth == CV_32F )
{
const float* dataA = (const float*)srcA.data;
const float* dataB = (const float*)srcB.data;
float* dataC = (float*)dst.data;
float eps = FLT_EPSILON; // prevent div0 problems
size_t stepA = srcA.step/sizeof(dataA[0]);
size_t stepB = srcB.step/sizeof(dataB[0]);
size_t stepC = dst.step/sizeof(dataC[0]);
if( !is_1d && cn == 1 )
{
for( k = 0; k < (cols % 2 ? 1 : 2); k++ )
{
if( k == 1 )
dataA += cols - 1, dataB += cols - 1, dataC += cols - 1;
dataC[0] = dataA[0] / (dataB[0] + eps);
if( rows % 2 == 0 )
dataC[(rows-1)*stepC] = dataA[(rows-1)*stepA] / (dataB[(rows-1)*stepB] + eps);
if( !conjB )
for( j = 1; j <= rows - 2; j += 2 )
{
double denom = (double)dataB[j*stepB]*dataB[j*stepB] +
(double)dataB[(j+1)*stepB]*dataB[(j+1)*stepB] + (double)eps;
double re = (double)dataA[j*stepA]*dataB[j*stepB] +
(double)dataA[(j+1)*stepA]*dataB[(j+1)*stepB];
double im = (double)dataA[(j+1)*stepA]*dataB[j*stepB] -
(double)dataA[j*stepA]*dataB[(j+1)*stepB];
dataC[j*stepC] = (float)(re / denom);
dataC[(j+1)*stepC] = (float)(im / denom);
}
else
for( j = 1; j <= rows - 2; j += 2 )
{
double denom = (double)dataB[j*stepB]*dataB[j*stepB] +
(double)dataB[(j+1)*stepB]*dataB[(j+1)*stepB] + (double)eps;
double re = (double)dataA[j*stepA]*dataB[j*stepB] -
(double)dataA[(j+1)*stepA]*dataB[(j+1)*stepB];
double im = (double)dataA[(j+1)*stepA]*dataB[j*stepB] +
(double)dataA[j*stepA]*dataB[(j+1)*stepB];
dataC[j*stepC] = (float)(re / denom);
dataC[(j+1)*stepC] = (float)(im / denom);
}
if( k == 1 )
dataA -= cols - 1, dataB -= cols - 1, dataC -= cols - 1;
}
}
for( ; rows--; dataA += stepA, dataB += stepB, dataC += stepC )
{
if( is_1d && cn == 1 )
{
dataC[0] = dataA[0] / (dataB[0] + eps);
if( cols % 2 == 0 )
dataC[j1] = dataA[j1] / (dataB[j1] + eps);
}
if( !conjB )
for( j = j0; j < j1; j += 2 )
{
double denom = (double)(dataB[j]*dataB[j] + dataB[j+1]*dataB[j+1] + eps);
double re = (double)(dataA[j]*dataB[j] + dataA[j+1]*dataB[j+1]);
double im = (double)(dataA[j+1]*dataB[j] - dataA[j]*dataB[j+1]);
dataC[j] = (float)(re / denom);
dataC[j+1] = (float)(im / denom);
}
else
for( j = j0; j < j1; j += 2 )
{
double denom = (double)(dataB[j]*dataB[j] + dataB[j+1]*dataB[j+1] + eps);
double re = (double)(dataA[j]*dataB[j] - dataA[j+1]*dataB[j+1]);
double im = (double)(dataA[j+1]*dataB[j] + dataA[j]*dataB[j+1]);
dataC[j] = (float)(re / denom);
dataC[j+1] = (float)(im / denom);
}
}
}
else
{
const double* dataA = (const double*)srcA.data;
const double* dataB = (const double*)srcB.data;
double* dataC = (double*)dst.data;
double eps = DBL_EPSILON; // prevent div0 problems
size_t stepA = srcA.step/sizeof(dataA[0]);
size_t stepB = srcB.step/sizeof(dataB[0]);
size_t stepC = dst.step/sizeof(dataC[0]);
if( !is_1d && cn == 1 )
{
for( k = 0; k < (cols % 2 ? 1 : 2); k++ )
{
if( k == 1 )
dataA += cols - 1, dataB += cols - 1, dataC += cols - 1;
dataC[0] = dataA[0] / (dataB[0] + eps);
if( rows % 2 == 0 )
dataC[(rows-1)*stepC] = dataA[(rows-1)*stepA] / (dataB[(rows-1)*stepB] + eps);
if( !conjB )
for( j = 1; j <= rows - 2; j += 2 )
{
double denom = dataB[j*stepB]*dataB[j*stepB] +
dataB[(j+1)*stepB]*dataB[(j+1)*stepB] + eps;
double re = dataA[j*stepA]*dataB[j*stepB] +
dataA[(j+1)*stepA]*dataB[(j+1)*stepB];
double im = dataA[(j+1)*stepA]*dataB[j*stepB] -
dataA[j*stepA]*dataB[(j+1)*stepB];
dataC[j*stepC] = re / denom;
dataC[(j+1)*stepC] = im / denom;
}
else
for( j = 1; j <= rows - 2; j += 2 )
{
double denom = dataB[j*stepB]*dataB[j*stepB] +
dataB[(j+1)*stepB]*dataB[(j+1)*stepB] + eps;
double re = dataA[j*stepA]*dataB[j*stepB] -
dataA[(j+1)*stepA]*dataB[(j+1)*stepB];
double im = dataA[(j+1)*stepA]*dataB[j*stepB] +
dataA[j*stepA]*dataB[(j+1)*stepB];
dataC[j*stepC] = re / denom;
dataC[(j+1)*stepC] = im / denom;
}
if( k == 1 )
dataA -= cols - 1, dataB -= cols - 1, dataC -= cols - 1;
}
}
for( ; rows--; dataA += stepA, dataB += stepB, dataC += stepC )
{
if( is_1d && cn == 1 )
{
dataC[0] = dataA[0] / (dataB[0] + eps);
if( cols % 2 == 0 )
dataC[j1] = dataA[j1] / (dataB[j1] + eps);
}
if( !conjB )
for( j = j0; j < j1; j += 2 )
{
double denom = dataB[j]*dataB[j] + dataB[j+1]*dataB[j+1] + eps;
double re = dataA[j]*dataB[j] + dataA[j+1]*dataB[j+1];
double im = dataA[j+1]*dataB[j] - dataA[j]*dataB[j+1];
dataC[j] = re / denom;
dataC[j+1] = im / denom;
}
else
for( j = j0; j < j1; j += 2 )
{
double denom = dataB[j]*dataB[j] + dataB[j+1]*dataB[j+1] + eps;
double re = dataA[j]*dataB[j] - dataA[j+1]*dataB[j+1];
double im = dataA[j+1]*dataB[j] + dataA[j]*dataB[j+1];
dataC[j] = re / denom;
dataC[j+1] = im / denom;
}
}
}
}
static void fftShift(InputOutputArray _out)
{
Mat out = _out.getMat();
if(out.rows == 1 && out.cols == 1)
{
// trivially shifted.
return;
}
std::vector<Mat> planes;
split(out, planes);
int xMid = out.cols >> 1;
int yMid = out.rows >> 1;
bool is_1d = xMid == 0 || yMid == 0;
if(is_1d)
{
xMid = xMid + yMid;
for(size_t i = 0; i < planes.size(); i++)
{
Mat tmp;
Mat half0(planes[i], Rect(0, 0, xMid, 1));
Mat half1(planes[i], Rect(xMid, 0, xMid, 1));
half0.copyTo(tmp);
half1.copyTo(half0);
tmp.copyTo(half1);
}
}
else
{
for(size_t i = 0; i < planes.size(); i++)
{
// perform quadrant swaps...
Mat tmp;
Mat q0(planes[i], Rect(0, 0, xMid, yMid));
Mat q1(planes[i], Rect(xMid, 0, xMid, yMid));
Mat q2(planes[i], Rect(0, yMid, xMid, yMid));
Mat q3(planes[i], Rect(xMid, yMid, xMid, yMid));
q0.copyTo(tmp);
q3.copyTo(q0);
tmp.copyTo(q3);
q1.copyTo(tmp);
q2.copyTo(q1);
tmp.copyTo(q2);
}
}
merge(planes, out);
}
static Point2d weightedCentroid(InputArray _src, cv::Point peakLocation, cv::Size weightBoxSize, double* response)
{
Mat src = _src.getMat();
int type = src.type();
CV_Assert( type == CV_32FC1 || type == CV_64FC1 );
int minr = peakLocation.y - (weightBoxSize.height >> 1);
int maxr = peakLocation.y + (weightBoxSize.height >> 1);
int minc = peakLocation.x - (weightBoxSize.width >> 1);
int maxc = peakLocation.x + (weightBoxSize.width >> 1);
Point2d centroid;
double sumIntensity = 0.0;
// clamp the values to min and max if needed.
if(minr < 0)
{
minr = 0;
}
if(minc < 0)
{
minc = 0;
}
if(maxr > src.rows - 1)
{
maxr = src.rows - 1;
}
if(maxc > src.cols - 1)
{
maxc = src.cols - 1;
}
if(type == CV_32FC1)
{
const float* dataIn = (const float*)src.data;
dataIn += minr*src.cols;
for(int y = minr; y <= maxr; y++)
{
for(int x = minc; x <= maxc; x++)
{
centroid.x += (double)x*dataIn[x];
centroid.y += (double)y*dataIn[x];
sumIntensity += (double)dataIn[x];
}
dataIn += src.cols;
}
}
else
{
const double* dataIn = (const double*)src.data;
dataIn += minr*src.cols;
for(int y = minr; y <= maxr; y++)
{
for(int x = minc; x <= maxc; x++)
{
centroid.x += (double)x*dataIn[x];
centroid.y += (double)y*dataIn[x];
sumIntensity += dataIn[x];
}
dataIn += src.cols;
}
}
if(response)
*response = sumIntensity;
sumIntensity += DBL_EPSILON; // prevent div0 problems...
centroid.x /= sumIntensity;
centroid.y /= sumIntensity;
return centroid;
}
}
cv::Point2d cv::phaseCorrelate(InputArray _src1, InputArray _src2, InputArray _window, double* response)
{
Mat src1 = _src1.getMat();
Mat src2 = _src2.getMat();
Mat window = _window.getMat();
CV_Assert( src1.type() == src2.type());
CV_Assert( src1.type() == CV_32FC1 || src1.type() == CV_64FC1 );
CV_Assert( src1.size == src2.size);
if(!window.empty())
{
CV_Assert( src1.type() == window.type());
CV_Assert( src1.size == window.size);
}
int M = getOptimalDFTSize(src1.rows);
int N = getOptimalDFTSize(src1.cols);
Mat padded1, padded2, paddedWin;
if(M != src1.rows || N != src1.cols)
{
copyMakeBorder(src1, padded1, 0, M - src1.rows, 0, N - src1.cols, BORDER_CONSTANT, Scalar::all(0));
copyMakeBorder(src2, padded2, 0, M - src2.rows, 0, N - src2.cols, BORDER_CONSTANT, Scalar::all(0));
if(!window.empty())
{
copyMakeBorder(window, paddedWin, 0, M - window.rows, 0, N - window.cols, BORDER_CONSTANT, Scalar::all(0));
}
}
else
{
padded1 = src1;
padded2 = src2;
paddedWin = window;
}
Mat FFT1, FFT2, P, Pm, C;
// perform window multiplication if available
if(!paddedWin.empty())
{
// apply window to both images before proceeding...
multiply(paddedWin, padded1, padded1);
multiply(paddedWin, padded2, padded2);
}
// execute phase correlation equation
// Reference: http://en.wikipedia.org/wiki/Phase_correlation
dft(padded1, FFT1, DFT_REAL_OUTPUT);
dft(padded2, FFT2, DFT_REAL_OUTPUT);
mulSpectrums(FFT1, FFT2, P, 0, true);
magSpectrums(P, Pm);
divSpectrums(P, Pm, C, 0, false); // FF* / |FF*| (phase correlation equation completed here...)
idft(C, C); // gives us the nice peak shift location...
fftShift(C); // shift the energy to the center of the frame.
// locate the highest peak
Point peakLoc;
minMaxLoc(C, NULL, NULL, NULL, &peakLoc);
// get the phase shift with sub-pixel accuracy, 5x5 window seems about right here...
Point2d t;
t = weightedCentroid(C, peakLoc, Size(5, 5), response);
// max response is M*N (not exactly, might be slightly larger due to rounding errors)
if(response)
*response /= M*N;
// adjust shift relative to image center...
Point2d center((double)padded1.cols / 2.0, (double)padded1.rows / 2.0);
return (center - t);
}
void cv::createHanningWindow(OutputArray _dst, cv::Size winSize, int type)
{
CV_Assert( type == CV_32FC1 || type == CV_64FC1 );
_dst.create(winSize, type);
Mat dst = _dst.getMat();
int rows = dst.rows, cols = dst.cols;
AutoBuffer<double> _wc(cols);
double * const wc = (double *)_wc;
double coeff0 = 2.0 * CV_PI / (double)(cols - 1), coeff1 = 2.0f * CV_PI / (double)(rows - 1);
for(int j = 0; j < cols; j++)
wc[j] = 0.5 * (1.0 - cos(coeff0 * j));
if(dst.depth() == CV_32F)
{
for(int i = 0; i < rows; i++)
{
float* dstData = dst.ptr<float>(i);
double wr = 0.5 * (1.0 - cos(coeff1 * i));
for(int j = 0; j < cols; j++)
dstData[j] = (float)(wr * wc[j]);
}
}
else
{
for(int i = 0; i < rows; i++)
{
double* dstData = dst.ptr<double>(i);
double wr = 0.5 * (1.0 - cos(coeff1 * i));
for(int j = 0; j < cols; j++)
dstData[j] = wr * wc[j];
}
}
// perform batch sqrt for SSE performance gains
cv::sqrt(dst, dst);
}