/*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_SUPERRES_HPP #define OPENCV_SUPERRES_HPP #include "opencv2/core.hpp" #include "opencv2/superres/optical_flow.hpp" /** @defgroup superres Super Resolution The Super Resolution module contains a set of functions and classes that can be used to solve the problem of resolution enhancement. There are a few methods implemented, most of them are described in the papers @cite Farsiu03 and @cite Mitzel09 . */ namespace cv { namespace superres { //! @addtogroup superres //! @{ class CV_EXPORTS FrameSource { public: virtual ~FrameSource(); virtual void nextFrame(OutputArray frame) = 0; virtual void reset() = 0; }; CV_EXPORTS Ptr createFrameSource_Empty(); CV_EXPORTS Ptr createFrameSource_Video(const String& fileName); CV_EXPORTS Ptr createFrameSource_Video_CUDA(const String& fileName); CV_EXPORTS Ptr createFrameSource_Camera(int deviceId = 0); /** @brief Base class for Super Resolution algorithms. The class is only used to define the common interface for the whole family of Super Resolution algorithms. */ class CV_EXPORTS SuperResolution : public cv::Algorithm, public FrameSource { public: /** @brief Set input frame source for Super Resolution algorithm. @param frameSource Input frame source */ void setInput(const Ptr& frameSource); /** @brief Process next frame from input and return output result. @param frame Output result */ void nextFrame(OutputArray frame) CV_OVERRIDE; void reset() CV_OVERRIDE; /** @brief Clear all inner buffers. */ virtual void collectGarbage(); //! @brief Scale factor /** @see setScale */ virtual int getScale() const = 0; /** @copybrief getScale @see getScale */ virtual void setScale(int val) = 0; //! @brief Iterations count /** @see setIterations */ virtual int getIterations() const = 0; /** @copybrief getIterations @see getIterations */ virtual void setIterations(int val) = 0; //! @brief Asymptotic value of steepest descent method /** @see setTau */ virtual double getTau() const = 0; /** @copybrief getTau @see getTau */ virtual void setTau(double val) = 0; //! @brief Weight parameter to balance data term and smoothness term /** @see setLambda */ virtual double getLambda() const = 0; /** @copybrief getLambda @see getLambda */ virtual void setLambda(double val) = 0; //! @brief Parameter of spacial distribution in Bilateral-TV /** @see setAlpha */ virtual double getAlpha() const = 0; /** @copybrief getAlpha @see getAlpha */ virtual void setAlpha(double val) = 0; //! @brief Kernel size of Bilateral-TV filter /** @see setKernelSize */ virtual int getKernelSize() const = 0; /** @copybrief getKernelSize @see getKernelSize */ virtual void setKernelSize(int val) = 0; //! @brief Gaussian blur kernel size /** @see setBlurKernelSize */ virtual int getBlurKernelSize() const = 0; /** @copybrief getBlurKernelSize @see getBlurKernelSize */ virtual void setBlurKernelSize(int val) = 0; //! @brief Gaussian blur sigma /** @see setBlurSigma */ virtual double getBlurSigma() const = 0; /** @copybrief getBlurSigma @see getBlurSigma */ virtual void setBlurSigma(double val) = 0; //! @brief Radius of the temporal search area /** @see setTemporalAreaRadius */ virtual int getTemporalAreaRadius() const = 0; /** @copybrief getTemporalAreaRadius @see getTemporalAreaRadius */ virtual void setTemporalAreaRadius(int val) = 0; //! @brief Dense optical flow algorithm /** @see setOpticalFlow */ virtual Ptr getOpticalFlow() const = 0; /** @copybrief getOpticalFlow @see getOpticalFlow */ virtual void setOpticalFlow(const Ptr &val) = 0; protected: SuperResolution(); virtual void initImpl(Ptr& frameSource) = 0; virtual void processImpl(Ptr& frameSource, OutputArray output) = 0; bool isUmat_; private: Ptr frameSource_; bool firstCall_; }; /** @brief Create Bilateral TV-L1 Super Resolution. This class implements Super Resolution algorithm described in the papers @cite Farsiu03 and @cite Mitzel09 . Here are important members of the class that control the algorithm, which you can set after constructing the class instance: - **int scale** Scale factor. - **int iterations** Iteration count. - **double tau** Asymptotic value of steepest descent method. - **double lambda** Weight parameter to balance data term and smoothness term. - **double alpha** Parameter of spacial distribution in Bilateral-TV. - **int btvKernelSize** Kernel size of Bilateral-TV filter. - **int blurKernelSize** Gaussian blur kernel size. - **double blurSigma** Gaussian blur sigma. - **int temporalAreaRadius** Radius of the temporal search area. - **Ptr\ opticalFlow** Dense optical flow algorithm. */ CV_EXPORTS Ptr createSuperResolution_BTVL1(); CV_EXPORTS Ptr createSuperResolution_BTVL1_CUDA(); //! @} superres } } #endif // OPENCV_SUPERRES_HPP