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Editing: superres.hpp

/*M///////////////////////////////////////////////////////////////////////////////////////
//
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//
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//  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.
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// 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.
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//     this list of conditions and the following disclaimer in the documentation
//     and/or other materials provided with the distribution.
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//   * The name of the copyright holders may not be used to endorse or promote products
//     derived from this software without specific prior written permission.
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// 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,
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//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 descibed 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<FrameSource> createFrameSource_Empty();

CV_EXPORTS Ptr<FrameSource> createFrameSource_Video(const String& fileName);
        CV_EXPORTS Ptr<FrameSource> createFrameSource_Video_CUDA(const String& fileName);

CV_EXPORTS Ptr<FrameSource> 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>& frameSource);

/** @brief Process next frame from input and return output result.

@param frame Output result
             */
            void nextFrame(OutputArray frame);
            void reset();

/** @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 setLabmda */
            virtual double getLabmda() const = 0;
            /** @copybrief getLabmda @see getLabmda */
            virtual void setLabmda(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<cv::superres::DenseOpticalFlowExt> getOpticalFlow() const = 0;
            /** @copybrief getOpticalFlow @see getOpticalFlow */
            virtual void setOpticalFlow(const Ptr<cv::superres::DenseOpticalFlowExt> &val) = 0;

protected:
            SuperResolution();

virtual void initImpl(Ptr<FrameSource>& frameSource) = 0;
            virtual void processImpl(Ptr<FrameSource>& frameSource, OutputArray output) = 0;

bool isUmat_;

private:
            Ptr<FrameSource> 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\<DenseOpticalFlowExt\> opticalFlow** Dense optical flow algorithm.
         */
        CV_EXPORTS Ptr<SuperResolution> createSuperResolution_BTVL1();
        CV_EXPORTS Ptr<SuperResolution> createSuperResolution_BTVL1_CUDA();

//! @} superres

}
}

#endif // OPENCV_SUPERRES_HPP