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