/*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. // // // License Agreement // For Open Source Computer Vision Library // // Copyright (C) 2000-2008, Intel Corporation, all rights reserved. // Copyright (C) 2009, Willow Garage Inc., 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 Intel Corporation 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; // 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*/ #ifndef __OPENCV_TEST_INTERPOLATION_HPP__ #define __OPENCV_TEST_INTERPOLATION_HPP__ #include "opencv2/core.hpp" #include "opencv2/imgproc.hpp" template <typename T> T readVal(const cv::Mat& src, int y, int x, int c, int border_type, cv::Scalar borderVal = cv::Scalar()) { if (border_type == cv::BORDER_CONSTANT) return (y >= 0 && y < src.rows && x >= 0 && x < src.cols) ? src.at<T>(y, x * src.channels() + c) : cv::saturate_cast<T>(borderVal.val[c]); return src.at<T>(cv::borderInterpolate(y, src.rows, border_type), cv::borderInterpolate(x, src.cols, border_type) * src.channels() + c); } template <typename T> struct NearestInterpolator { static T getValue(const cv::Mat& src, float y, float x, int c, int border_type, cv::Scalar borderVal = cv::Scalar()) { return readVal<T>(src, int(y), int(x), c, border_type, borderVal); } }; template <typename T> struct LinearInterpolator { static T getValue(const cv::Mat& src, float y, float x, int c, int border_type, cv::Scalar borderVal = cv::Scalar()) { int x1 = cvFloor(x); int y1 = cvFloor(y); int x2 = x1 + 1; int y2 = y1 + 1; float res = 0; res += readVal<T>(src, y1, x1, c, border_type, borderVal) * ((x2 - x) * (y2 - y)); res += readVal<T>(src, y1, x2, c, border_type, borderVal) * ((x - x1) * (y2 - y)); res += readVal<T>(src, y2, x1, c, border_type, borderVal) * ((x2 - x) * (y - y1)); res += readVal<T>(src, y2, x2, c, border_type, borderVal) * ((x - x1) * (y - y1)); return cv::saturate_cast<T>(res); } }; template <typename T> struct CubicInterpolator { static float bicubicCoeff(float x_) { float x = fabsf(x_); if (x <= 1.0f) { return x * x * (1.5f * x - 2.5f) + 1.0f; } else if (x < 2.0f) { return x * (x * (-0.5f * x + 2.5f) - 4.0f) + 2.0f; } else { return 0.0f; } } static T getValue(const cv::Mat& src, float y, float x, int c, int border_type, cv::Scalar borderVal = cv::Scalar()) { const float xmin = ceilf(x - 2.0f); const float xmax = floorf(x + 2.0f); const float ymin = ceilf(y - 2.0f); const float ymax = floorf(y + 2.0f); float sum = 0.0f; float wsum = 0.0f; for (float cy = ymin; cy <= ymax; cy += 1.0f) { for (float cx = xmin; cx <= xmax; cx += 1.0f) { const float w = bicubicCoeff(x - cx) * bicubicCoeff(y - cy); sum += w * readVal<T>(src, (int) floorf(cy), (int) floorf(cx), c, border_type, borderVal); wsum += w; } } float res = (!wsum)? 0 : sum / wsum; return cv::saturate_cast<T>(res); } }; #endif // __OPENCV_TEST_INTERPOLATION_HPP__