/*M/////////////////////////////////////////////////////////////////////////////////////// // // IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING. // // By downloading, copying, installing or using the software you agree to this license. // If you do not agree to this license, do not download, install, // copy or use the software. // // Copyright (C) 2013, Alfonso Sanchez-Beato, all rights reserved. // Third party copyrights are property of their respective owners. // // Redistribution and use in source and binary forms, with or without modification, // are permitted provided that the following conditions are met: // // * Redistribution's of source code must retain the above copyright notice, // this list of conditions and the following disclaimer. // // * Redistribution's 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. // // * The name of the copyright holders may not 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 contributors be liable for any direct, // indirect, incidental, special, exemplary, or consequential damages // (including, but not limited to, procurement of substitute goods or services; // loss of use, data, or profits; or business interruption) however caused // and on any theory of liability, whether in contract, strict 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. // //M*/ #include "precomp.hpp" #include "opencv2/reg/mappergradsimilar.hpp" #include "opencv2/reg/mapaffine.hpp" namespace cv { namespace reg { //////////////////////////////////////////////////////////////////////////////////////////////////// MapperGradSimilar::MapperGradSimilar() { } //////////////////////////////////////////////////////////////////////////////////////////////////// MapperGradSimilar::~MapperGradSimilar() { } //////////////////////////////////////////////////////////////////////////////////////////////////// cv::Ptr<Map> MapperGradSimilar::calculate( InputArray _img1, InputArray image2, cv::Ptr<Map> init) const { Mat img1 = _img1.getMat(); Mat gradx, grady, imgDiff; Mat img2; CV_DbgAssert(img1.size() == image2.size()); CV_DbgAssert(img1.channels() == image2.channels()); CV_DbgAssert(img1.channels() == 1 || img1.channels() == 3); if(!init.empty()) { // We have initial values for the registration: we move img2 to that initial reference init->inverseWarp(image2, img2); } else { img2 = image2.getMat(); } // Get gradient in all channels gradient(img1, img2, gradx, grady, imgDiff); // Matrices with reference frame coordinates Mat grid_r, grid_c; grid(img1, grid_r, grid_c); // Calculate parameters using least squares Matx<double, 4, 4> A; Vec<double, 4> b; // For each value in A, all the matrix elements are added and then the channels are also added, // so we have two calls to "sum". The result can be found in the first element of the final // Scalar object. Mat xIx_p_yIy = grid_c.mul(gradx); xIx_p_yIy += grid_r.mul(grady); Mat yIx_m_xIy = grid_r.mul(gradx); yIx_m_xIy -= grid_c.mul(grady); A(0, 0) = sum(sum(sqr(xIx_p_yIy)))[0]; A(0, 1) = sum(sum(xIx_p_yIy.mul(yIx_m_xIy)))[0]; A(0, 2) = sum(sum(gradx.mul(xIx_p_yIy)))[0]; A(0, 3) = sum(sum(grady.mul(xIx_p_yIy)))[0]; A(1, 1) = sum(sum(sqr(yIx_m_xIy)))[0]; A(1, 2) = sum(sum(gradx.mul(yIx_m_xIy)))[0]; A(1, 3) = sum(sum(grady.mul(yIx_m_xIy)))[0]; A(2, 2) = sum(sum(sqr(gradx)))[0]; A(2, 3) = sum(sum(gradx.mul(grady)))[0]; A(3, 3) = sum(sum(sqr(grady)))[0]; // Lower half values (A is symmetric) A(1, 0) = A(0, 1); A(2, 0) = A(0, 2); A(3, 0) = A(0, 3); A(2, 1) = A(1, 2); A(3, 1) = A(1, 3); A(3, 2) = A(2, 3); // Calculation of b b(0) = -sum(sum(imgDiff.mul(xIx_p_yIy)))[0]; b(1) = -sum(sum(imgDiff.mul(yIx_m_xIy)))[0]; b(2) = -sum(sum(imgDiff.mul(gradx)))[0]; b(3) = -sum(sum(imgDiff.mul(grady)))[0]; // Calculate affine transformation. We use Cholesky decomposition, as A is symmetric. Vec<double, 4> k = A.inv(DECOMP_CHOLESKY)*b; Matx<double, 2, 2> linTr(k(0) + 1., k(1), -k(1), k(0) + 1.); Vec<double, 2> shift(k(2), k(3)); if(init.empty()) { return Ptr<Map>(new MapAffine(linTr, shift)); } else { Ptr<MapAffine> newTr(new MapAffine(linTr, shift)); MapAffine* initPtr = dynamic_cast<MapAffine*>(init.get()); Ptr<MapAffine> oldTr(new MapAffine(initPtr->getLinTr(), initPtr->getShift())); oldTr->compose(newTr); return oldTr; } } //////////////////////////////////////////////////////////////////////////////////////////////////// cv::Ptr<Map> MapperGradSimilar::getMap() const { return cv::Ptr<Map>(new MapAffine()); } }} // namespace cv::reg