132 lines
4.9 KiB
C++
132 lines
4.9 KiB
C++
/*M///////////////////////////////////////////////////////////////////////////////////////
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//
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// IMPORTANT: READ BEFORE DOWNLOADING, COPYING, INSTALLING OR USING.
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//
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// By downloading, copying, installing or using the software you agree to this license.
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// If you do not agree to this license, do not download, install,
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// copy or use the software.
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//
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//
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// License Agreement
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// For Open Source Computer Vision Library
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//
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// Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
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// Copyright (C) 2009, Willow Garage Inc., all rights reserved.
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// Third party copyrights are property of their respective owners.
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//
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// Redistribution and use in source and binary forms, with or without modification,
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// are permitted provided that the following conditions are met:
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//
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// * Redistribution's of source code must retain the above copyright notice,
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// this list of conditions and the following disclaimer.
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//
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// * Redistribution's in binary form must reproduce the above copyright notice,
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// this list of conditions and the following disclaimer in the documentation
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// and/or other materials provided with the distribution.
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//
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// * The name of the copyright holders may not be used to endorse or promote products
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// derived from this software without specific prior written permission.
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//
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// This software is provided by the copyright holders and contributors "as is" and
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// any express or implied warranties, including, but not limited to, the implied
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// warranties of merchantability and fitness for a particular purpose are disclaimed.
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// In no event shall the Intel Corporation or contributors be liable for any direct,
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// indirect, incidental, special, exemplary, or consequential damages
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// (including, but not limited to, procurement of substitute goods or services;
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// loss of use, data, or profits; or business interruption) however caused
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// and on any theory of liability, whether in contract, strict liability,
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// or tort (including negligence or otherwise) arising in any way out of
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// the use of this software, even if advised of the possibility of such damage.
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//
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//M*/
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#ifndef __OPENCV_TEST_INTERPOLATION_HPP__
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#define __OPENCV_TEST_INTERPOLATION_HPP__
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#include "opencv2/core.hpp"
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#include "opencv2/imgproc.hpp"
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template <typename T> T readVal(const cv::Mat& src, int y, int x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
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{
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if (border_type == cv::BORDER_CONSTANT)
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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]);
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return src.at<T>(cv::borderInterpolate(y, src.rows, border_type), cv::borderInterpolate(x, src.cols, border_type) * src.channels() + c);
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}
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template <typename T> struct NearestInterpolator
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{
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static T getValue(const cv::Mat& src, float y, float x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
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{
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return readVal<T>(src, int(y), int(x), c, border_type, borderVal);
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}
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};
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template <typename T> struct LinearInterpolator
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{
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static T getValue(const cv::Mat& src, float y, float x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
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{
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int x1 = cvFloor(x);
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int y1 = cvFloor(y);
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int x2 = x1 + 1;
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int y2 = y1 + 1;
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float res = 0;
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res += readVal<T>(src, y1, x1, c, border_type, borderVal) * ((x2 - x) * (y2 - y));
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res += readVal<T>(src, y1, x2, c, border_type, borderVal) * ((x - x1) * (y2 - y));
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res += readVal<T>(src, y2, x1, c, border_type, borderVal) * ((x2 - x) * (y - y1));
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res += readVal<T>(src, y2, x2, c, border_type, borderVal) * ((x - x1) * (y - y1));
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return cv::saturate_cast<T>(res);
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}
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};
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template <typename T> struct CubicInterpolator
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{
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static float bicubicCoeff(float x_)
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{
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float x = fabsf(x_);
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if (x <= 1.0f)
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{
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return x * x * (1.5f * x - 2.5f) + 1.0f;
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}
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else if (x < 2.0f)
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{
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return x * (x * (-0.5f * x + 2.5f) - 4.0f) + 2.0f;
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}
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else
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{
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return 0.0f;
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}
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}
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static T getValue(const cv::Mat& src, float y, float x, int c, int border_type, cv::Scalar borderVal = cv::Scalar())
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{
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const float xmin = ceilf(x - 2.0f);
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const float xmax = floorf(x + 2.0f);
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const float ymin = ceilf(y - 2.0f);
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const float ymax = floorf(y + 2.0f);
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float sum = 0.0f;
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float wsum = 0.0f;
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for (float cy = ymin; cy <= ymax; cy += 1.0f)
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{
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for (float cx = xmin; cx <= xmax; cx += 1.0f)
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{
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const float w = bicubicCoeff(x - cx) * bicubicCoeff(y - cy);
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sum += w * readVal<T>(src, (int) floorf(cy), (int) floorf(cx), c, border_type, borderVal);
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wsum += w;
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}
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}
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float res = (!wsum)? 0 : sum / wsum;
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return cv::saturate_cast<T>(res);
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}
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};
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#endif // __OPENCV_TEST_INTERPOLATION_HPP__
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