/*#******************************************************************************
 ** 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.
 **
 **
 ** HVStools : interfaces allowing OpenCV users to integrate Human Vision System models. Presented models originate from Jeanny Herault's original research and have been reused and adapted by the author&collaborators for computed vision applications since his thesis with Alice Caplier at Gipsa-Lab.
 ** Use: extract still images & image sequences features, from contours details to motion spatio-temporal features, etc. for high level visual scene analysis. Also contribute to image enhancement/compression such as tone mapping.
 **
 ** Maintainers : Listic lab (code author current affiliation & applications) and Gipsa Lab (original research origins & applications)
 **
 **  Creation - enhancement process 2007-2011
 **      Author: Alexandre Benoit (benoit.alexandre.vision@gmail.com), LISTIC lab, Annecy le vieux, France
 **
 ** Theses algorithm have been developped by Alexandre BENOIT since his thesis with Alice Caplier at Gipsa-Lab (www.gipsa-lab.inpg.fr) and the research he pursues at LISTIC Lab (www.listic.univ-savoie.fr).
 ** Refer to the following research paper for more information:
 ** Benoit A., Caplier A., Durette B., Herault, J., "USING HUMAN VISUAL SYSTEM MODELING FOR BIO-INSPIRED LOW LEVEL IMAGE PROCESSING", Elsevier, Computer Vision and Image Understanding 114 (2010), pp. 758-773, DOI: http://dx.doi.org/10.1016/j.cviu.2010.01.011
 ** This work have been carried out thanks to Jeanny Herault who's research and great discussions are the basis of all this work, please take a look at his book:
 ** Vision: Images, Signals and Neural Networks: Models of Neural Processing in Visual Perception (Progress in Neural Processing),By: Jeanny Herault, ISBN: 9814273686. WAPI (Tower ID): 113266891.
 **
 ** The retina filter includes the research contributions of phd/research collegues from which code has been redrawn by the author :
 ** _take a look at the retinacolor.hpp module to discover Brice Chaix de Lavarene color mosaicing/demosaicing and the reference paper:
 ** ====> B. Chaix de Lavarene, D. Alleysson, B. Durette, J. Herault (2007). "Efficient demosaicing through recursive filtering", IEEE International Conference on Image Processing ICIP 2007
 ** _take a look at imagelogpolprojection.hpp to discover retina spatial log sampling which originates from Barthelemy Durette phd with Jeanny Herault. A Retina / V1 cortex projection is also proposed and originates from Jeanny's discussions.
 ** ====> more informations in the above cited Jeanny Heraults's book.
 **
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 **               For Open Source Computer Vision Library
 **
 ** Copyright (C) 2000-2008, Intel Corporation, all rights reserved.
 ** Copyright (C) 2008-2011, Willow Garage Inc., all rights reserved.
 **
 **               For Human Visual System tools (hvstools)
 ** Copyright (C) 2007-2011, LISTIC Lab, Annecy le Vieux and GIPSA Lab, Grenoble, France, all rights reserved.
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 ** indirect, incidental, special, exemplary, or consequential damages
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/*
 * Retina.cpp
 *
 *  Created on: Jul 19, 2011
 *      Author: Alexandre Benoit
 */
#include "precomp.hpp"
#include "retinafilter.hpp"
#include <iostream>

namespace cv
{
    
Retina::Retina(const cv::Size inputSize)
{
    _retinaFilter = 0;
    _init(inputSize, true, RETINA_COLOR_BAYER, false);
}

Retina::Retina(const cv::Size inputSize, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod, const bool useRetinaLogSampling, const double reductionFactor, const double samplingStrenght)
{
    _retinaFilter = 0;
    _init(inputSize, colorMode, colorSamplingMethod, useRetinaLogSampling, reductionFactor, samplingStrenght);
};

Retina::~Retina()
{
    if (_retinaFilter)
        delete _retinaFilter;
}

void Retina::setColorSaturation(const bool saturateColors, const float colorSaturationValue)
{
	_retinaFilter->setColorSaturation(saturateColors, colorSaturationValue);
}

struct Retina::RetinaParameters Retina::getParameters(){return _retinaParameters;}


void Retina::setup(std::string retinaParameterFile, const bool applyDefaultSetupOnFailure)
{
    try
    {
        // opening retinaParameterFile in read mode
        cv::FileStorage fs(retinaParameterFile, cv::FileStorage::READ);
        setup(fs, applyDefaultSetupOnFailure);
    }catch(Exception &e)
    {
 	std::cout<<"Retina::setup: wrong/unappropriate xml parameter file : error report :`n=>"<<e.what()<<std::endl;
	if (applyDefaultSetupOnFailure)
	{
            std::cout<<"Retina::setup: resetting retina with default parameters"<<std::endl;
	    setupOPLandIPLParvoChannel();
	    setupIPLMagnoChannel();
	}
        else
        {
	    std::cout<<"=> keeping current parameters"<<std::endl;
        }
    }
}

void Retina::setup(cv::FileStorage &fs, const bool applyDefaultSetupOnFailure)
{
	try
	{
		// read parameters file if it exists or apply default setup if asked for
		if (!fs.isOpened())
		{
			std::cout<<"Retina::setup: provided parameters file could not be open... skeeping configuration"<<std::endl;
			return;
			// implicit else case : retinaParameterFile could be open (it exists at least)
		}
                // OPL and Parvo init first... update at the same time the parameters structure and the retina core
		cv::FileNode rootFn = fs.root(), currFn=rootFn["OPLandIPLparvo"];
		currFn["colorMode"]>>_retinaParameters.OPLandIplParvo.colorMode;
		currFn["normaliseOutput"]>>_retinaParameters.OPLandIplParvo.normaliseOutput;
		currFn["photoreceptorsLocalAdaptationSensitivity"]>>_retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity;
		currFn["photoreceptorsTemporalConstant"]>>_retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant;
		currFn["photoreceptorsSpatialConstant"]>>_retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant;
		currFn["horizontalCellsGain"]>>_retinaParameters.OPLandIplParvo.horizontalCellsGain;
		currFn["hcellsTemporalConstant"]>>_retinaParameters.OPLandIplParvo.hcellsTemporalConstant;
		currFn["hcellsSpatialConstant"]>>_retinaParameters.OPLandIplParvo.hcellsSpatialConstant;
		currFn["ganglionCellsSensitivity"]>>_retinaParameters.OPLandIplParvo.ganglionCellsSensitivity;
		setupOPLandIPLParvoChannel(_retinaParameters.OPLandIplParvo.colorMode, _retinaParameters.OPLandIplParvo.normaliseOutput, _retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity, _retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant, _retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant, _retinaParameters.OPLandIplParvo.horizontalCellsGain, _retinaParameters.OPLandIplParvo.hcellsTemporalConstant, _retinaParameters.OPLandIplParvo.hcellsSpatialConstant, _retinaParameters.OPLandIplParvo.ganglionCellsSensitivity);

		// init retina IPL magno setup... update at the same time the parameters structure and the retina core
		currFn=rootFn["IPLmagno"];
		currFn["normaliseOutput"]>>_retinaParameters.IplMagno.normaliseOutput;
		currFn["parasolCells_beta"]>>_retinaParameters.IplMagno.parasolCells_beta;
		currFn["parasolCells_tau"]>>_retinaParameters.IplMagno.parasolCells_tau;
		currFn["parasolCells_k"]>>_retinaParameters.IplMagno.parasolCells_k;
		currFn["amacrinCellsTemporalCutFrequency"]>>_retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency;
		currFn["V0CompressionParameter"]>>_retinaParameters.IplMagno.V0CompressionParameter;
		currFn["localAdaptintegration_tau"]>>_retinaParameters.IplMagno.localAdaptintegration_tau;
		currFn["localAdaptintegration_k"]>>_retinaParameters.IplMagno.localAdaptintegration_k;

		setupIPLMagnoChannel(_retinaParameters.IplMagno.normaliseOutput, _retinaParameters.IplMagno.parasolCells_beta, _retinaParameters.IplMagno.parasolCells_tau, _retinaParameters.IplMagno.parasolCells_k, _retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency,_retinaParameters.IplMagno.V0CompressionParameter, _retinaParameters.IplMagno.localAdaptintegration_tau, _retinaParameters.IplMagno.localAdaptintegration_k);

	}catch(Exception &e)
	{
		std::cout<<"Retina::setup: resetting retina with default parameters"<<std::endl;
		if (applyDefaultSetupOnFailure)
		{
			setupOPLandIPLParvoChannel();
			setupIPLMagnoChannel();
		}
		std::cout<<"Retina::setup: wrong/unappropriate xml parameter file : error report :`n=>"<<e.what()<<std::endl;
		std::cout<<"=> keeping current parameters"<<std::endl;
	}

	// report current configuration
	std::cout<<printSetup()<<std::endl;
}

void Retina::setup(cv::Retina::RetinaParameters newConfiguration)
{
    // simply copy structures
    memcpy(&_retinaParameters, &newConfiguration, sizeof(cv::Retina::RetinaParameters));
    // apply setup
    setupOPLandIPLParvoChannel(_retinaParameters.OPLandIplParvo.colorMode, _retinaParameters.OPLandIplParvo.normaliseOutput, _retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity, _retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant, _retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant, _retinaParameters.OPLandIplParvo.horizontalCellsGain, _retinaParameters.OPLandIplParvo.hcellsTemporalConstant, _retinaParameters.OPLandIplParvo.hcellsSpatialConstant, _retinaParameters.OPLandIplParvo.ganglionCellsSensitivity);
    setupIPLMagnoChannel(_retinaParameters.IplMagno.normaliseOutput, _retinaParameters.IplMagno.parasolCells_beta, _retinaParameters.IplMagno.parasolCells_tau, _retinaParameters.IplMagno.parasolCells_k, _retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency,_retinaParameters.IplMagno.V0CompressionParameter, _retinaParameters.IplMagno.localAdaptintegration_tau, _retinaParameters.IplMagno.localAdaptintegration_k);


}

const std::string Retina::printSetup()
{
	std::stringstream outmessage;

	// displaying OPL and IPL parvo setup
	outmessage<<"Current Retina instance setup :"
			<<"\nOPLandIPLparvo"<<"{"
			<< "\n==> colorMode : " << _retinaParameters.OPLandIplParvo.colorMode
			<< "\n==> normalizeParvoOutput :" << _retinaParameters.OPLandIplParvo.normaliseOutput
			<< "\n==> photoreceptorsLocalAdaptationSensitivity : " << _retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity
			<< "\n==> photoreceptorsTemporalConstant : " << _retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant
			<< "\n==> photoreceptorsSpatialConstant : " << _retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant
			<< "\n==> horizontalCellsGain : " << _retinaParameters.OPLandIplParvo.horizontalCellsGain
			<< "\n==> hcellsTemporalConstant : " << _retinaParameters.OPLandIplParvo.hcellsTemporalConstant
			<< "\n==> hcellsSpatialConstant : " << _retinaParameters.OPLandIplParvo.hcellsSpatialConstant
			<< "\n==> parvoGanglionCellsSensitivity : " << _retinaParameters.OPLandIplParvo.ganglionCellsSensitivity
			<<"}\n";

	// displaying IPL magno setup
	outmessage<<"Current Retina instance setup :"
			<<"\nIPLmagno"<<"{"
			<< "\n==> normaliseOutput : " << _retinaParameters.IplMagno.normaliseOutput
			<< "\n==> parasolCells_beta : " << _retinaParameters.IplMagno.parasolCells_beta
			<< "\n==> parasolCells_tau : " << _retinaParameters.IplMagno.parasolCells_tau
			<< "\n==> parasolCells_k : " << _retinaParameters.IplMagno.parasolCells_k
			<< "\n==> amacrinCellsTemporalCutFrequency : " << _retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency
			<< "\n==> V0CompressionParameter : " << _retinaParameters.IplMagno.V0CompressionParameter
			<< "\n==> localAdaptintegration_tau : " << _retinaParameters.IplMagno.localAdaptintegration_tau
			<< "\n==> localAdaptintegration_k : " << _retinaParameters.IplMagno.localAdaptintegration_k
			<<"}";
	return outmessage.str();
}

void Retina::write( std::string fs ) const
{
    FileStorage parametersSaveFile(fs, cv::FileStorage::WRITE );
    write(parametersSaveFile);
}

void Retina::write( FileStorage& fs ) const
{
	if (!fs.isOpened())
		return; // basic error case
	fs<<"OPLandIPLparvo"<<"{";
	fs << "colorMode" << _retinaParameters.OPLandIplParvo.colorMode;
	fs << "normaliseOutput" << _retinaParameters.OPLandIplParvo.normaliseOutput;
	fs << "photoreceptorsLocalAdaptationSensitivity" << _retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity;
	fs << "photoreceptorsTemporalConstant" << _retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant;
	fs << "photoreceptorsSpatialConstant" << _retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant;
	fs << "horizontalCellsGain" << _retinaParameters.OPLandIplParvo.horizontalCellsGain;
	fs << "hcellsTemporalConstant" << _retinaParameters.OPLandIplParvo.hcellsTemporalConstant;
	fs << "hcellsSpatialConstant" << _retinaParameters.OPLandIplParvo.hcellsSpatialConstant;
	fs << "ganglionCellsSensitivity" << _retinaParameters.OPLandIplParvo.ganglionCellsSensitivity;
	fs << "}";
	fs<<"IPLmagno"<<"{";
	fs << "normaliseOutput" << _retinaParameters.IplMagno.normaliseOutput;
	fs << "parasolCells_beta" << _retinaParameters.IplMagno.parasolCells_beta;
	fs << "parasolCells_tau" << _retinaParameters.IplMagno.parasolCells_tau;
	fs << "parasolCells_k" << _retinaParameters.IplMagno.parasolCells_k;
	fs << "amacrinCellsTemporalCutFrequency" << _retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency;
	fs << "V0CompressionParameter" << _retinaParameters.IplMagno.V0CompressionParameter;
	fs << "localAdaptintegration_tau" << _retinaParameters.IplMagno.localAdaptintegration_tau;
	fs << "localAdaptintegration_k" << _retinaParameters.IplMagno.localAdaptintegration_k;
	fs<<"}";
}

void Retina::setupOPLandIPLParvoChannel(const bool colorMode, const bool normaliseOutput, const float photoreceptorsLocalAdaptationSensitivity, const float photoreceptorsTemporalConstant, const float photoreceptorsSpatialConstant, const float horizontalCellsGain, const float HcellsTemporalConstant, const float HcellsSpatialConstant, const float ganglionCellsSensitivity)
{
	// retina core parameters setup
	_retinaFilter->setColorMode(colorMode);
	_retinaFilter->setPhotoreceptorsLocalAdaptationSensitivity(photoreceptorsLocalAdaptationSensitivity);
	_retinaFilter->setOPLandParvoParameters(0, photoreceptorsTemporalConstant, photoreceptorsSpatialConstant, horizontalCellsGain, HcellsTemporalConstant, HcellsSpatialConstant, ganglionCellsSensitivity);
	_retinaFilter->setParvoGanglionCellsLocalAdaptationSensitivity(ganglionCellsSensitivity);
	_retinaFilter->activateNormalizeParvoOutput_0_maxOutputValue(normaliseOutput);
	
        // update parameters struture

	_retinaParameters.OPLandIplParvo.colorMode = colorMode;
	_retinaParameters.OPLandIplParvo.normaliseOutput = normaliseOutput;
	_retinaParameters.OPLandIplParvo.photoreceptorsLocalAdaptationSensitivity = photoreceptorsLocalAdaptationSensitivity;
	_retinaParameters.OPLandIplParvo.photoreceptorsTemporalConstant = photoreceptorsTemporalConstant;
	_retinaParameters.OPLandIplParvo.photoreceptorsSpatialConstant = photoreceptorsSpatialConstant;
	_retinaParameters.OPLandIplParvo.horizontalCellsGain = horizontalCellsGain;
	_retinaParameters.OPLandIplParvo.hcellsTemporalConstant = HcellsTemporalConstant;
	_retinaParameters.OPLandIplParvo.hcellsSpatialConstant = HcellsSpatialConstant;
	_retinaParameters.OPLandIplParvo.ganglionCellsSensitivity = ganglionCellsSensitivity;

}

void Retina::setupIPLMagnoChannel(const bool normaliseOutput, const float parasolCells_beta, const float parasolCells_tau, const float parasolCells_k, const float amacrinCellsTemporalCutFrequency, const float V0CompressionParameter, const float localAdaptintegration_tau, const float localAdaptintegration_k)
{

	_retinaFilter->setMagnoCoefficientsTable(parasolCells_beta, parasolCells_tau, parasolCells_k, amacrinCellsTemporalCutFrequency, V0CompressionParameter, localAdaptintegration_tau, localAdaptintegration_k);
	_retinaFilter->activateNormalizeMagnoOutput_0_maxOutputValue(normaliseOutput);

        // update parameters struture
	_retinaParameters.IplMagno.normaliseOutput = normaliseOutput;
	_retinaParameters.IplMagno.parasolCells_beta = parasolCells_beta;
	_retinaParameters.IplMagno.parasolCells_tau = parasolCells_tau;
	_retinaParameters.IplMagno.parasolCells_k = parasolCells_k;
	_retinaParameters.IplMagno.amacrinCellsTemporalCutFrequency = amacrinCellsTemporalCutFrequency;
	_retinaParameters.IplMagno.V0CompressionParameter = V0CompressionParameter;
	_retinaParameters.IplMagno.localAdaptintegration_tau = localAdaptintegration_tau;
	_retinaParameters.IplMagno.localAdaptintegration_k = localAdaptintegration_k;
}

void Retina::run(const cv::Mat &inputMatToConvert)
{
	// first convert input image to the compatible format : std::valarray<float>
	const bool colorMode = _convertCvMat2ValarrayBuffer(inputMatToConvert, _inputBuffer);
	// process the retina
	if (!_retinaFilter->runFilter(_inputBuffer, colorMode, false, _retinaParameters.OPLandIplParvo.colorMode && colorMode, false))
		throw cv::Exception(-1, "Retina cannot be applied, wrong input buffer size", "Retina::run", "Retina.h", 0);
}

void Retina::getParvo(cv::Mat &retinaOutput_parvo)
{
	if (_retinaFilter->getColorMode())
	{
		// reallocate output buffer (if necessary)
		_convertValarrayBuffer2cvMat(_retinaFilter->getColorOutput(), _retinaFilter->getOutputNBrows(), _retinaFilter->getOutputNBcolumns(), true, retinaOutput_parvo);
	}else
	{
		// reallocate output buffer (if necessary)
		_convertValarrayBuffer2cvMat(_retinaFilter->getContours(), _retinaFilter->getOutputNBrows(), _retinaFilter->getOutputNBcolumns(), false, retinaOutput_parvo);
	}
	//retinaOutput_parvo/=255.0;
}
void Retina::getMagno(cv::Mat &retinaOutput_magno)
{
	// reallocate output buffer (if necessary)
	_convertValarrayBuffer2cvMat(_retinaFilter->getMovingContours(), _retinaFilter->getOutputNBrows(), _retinaFilter->getOutputNBcolumns(), false, retinaOutput_magno);
	//retinaOutput_magno/=255.0;
}

// original API level data accessors : copy buffers if size matches
void Retina::getMagno(std::valarray<float> &magnoOutputBufferCopy){if (magnoOutputBufferCopy.size()==_retinaFilter->getMovingContours().size()) magnoOutputBufferCopy = _retinaFilter->getMovingContours();}
void Retina::getParvo(std::valarray<float> &parvoOutputBufferCopy){if (parvoOutputBufferCopy.size()==_retinaFilter->getContours().size()) parvoOutputBufferCopy = _retinaFilter->getContours();}

// private method called by constructirs
void Retina::_init(const cv::Size inputSize, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod, const bool useRetinaLogSampling, const double reductionFactor, const double samplingStrenght)
{
	// basic error check
	if (inputSize.height*inputSize.width <= 0)
		throw cv::Exception(-1, "Bad retina size setup : size height and with must be superior to zero", "Retina::setup", "Retina.h", 0);

	unsigned int nbPixels=inputSize.height*inputSize.width;
	// resize buffers if size does not match
	_inputBuffer.resize(nbPixels*3); // buffer supports gray images but also 3 channels color buffers... (larger is better...)

	// allocate the retina model
        if (_retinaFilter)
           delete _retinaFilter;
	_retinaFilter = new RetinaFilter(inputSize.height, inputSize.width, colorMode, colorSamplingMethod, useRetinaLogSampling, reductionFactor, samplingStrenght);

	// prepare the default parameter XML file with default setup
        setup(_retinaParameters);

	// init retina
	_retinaFilter->clearAllBuffers();

	// report current configuration
	std::cout<<printSetup()<<std::endl;
}

void Retina::_convertValarrayBuffer2cvMat(const std::valarray<float> &grayMatrixToConvert, const unsigned int nbRows, const unsigned int nbColumns, const bool colorMode, cv::Mat &outBuffer)
{
	// fill output buffer with the valarray buffer
	const float *valarrayPTR=get_data(grayMatrixToConvert);
	if (!colorMode)
	{
		outBuffer.create(cv::Size(nbColumns, nbRows), CV_8U);
		for (unsigned int i=0;i<nbRows;++i)
		{
			for (unsigned int j=0;j<nbColumns;++j)
			{
				cv::Point2d pixel(j,i);
				outBuffer.at<unsigned char>(pixel)=(unsigned char)*(valarrayPTR++);
			}
		}
	}else
	{
		const unsigned int doubleNBpixels=_retinaFilter->getOutputNBpixels()*2;
		outBuffer.create(cv::Size(nbColumns, nbRows), CV_8UC3);
		for (unsigned int i=0;i<nbRows;++i)
		{
			for (unsigned int j=0;j<nbColumns;++j,++valarrayPTR)
			{
				cv::Point2d pixel(j,i);
				cv::Vec3b pixelValues;
				pixelValues[2]=(unsigned char)*(valarrayPTR);
				pixelValues[1]=(unsigned char)*(valarrayPTR+_retinaFilter->getOutputNBpixels());
				pixelValues[0]=(unsigned char)*(valarrayPTR+doubleNBpixels);

				outBuffer.at<cv::Vec3b>(pixel)=pixelValues;
			}
		}
	}
}

const bool Retina::_convertCvMat2ValarrayBuffer(const cv::Mat inputMatToConvert, std::valarray<float> &outputValarrayMatrix)
{
	// first check input consistency
	if (inputMatToConvert.empty())
		throw cv::Exception(-1, "Retina cannot be applied, input buffer is empty", "Retina::run", "Retina.h", 0);

	// retreive color mode from image input
	int imageNumberOfChannels = inputMatToConvert.channels();
	
        // convert to float AND fill the valarray buffer
	typedef float T; // define here the target pixel format, here, float
        const int dsttype = DataType<T>::depth; // output buffer is float format


	if(imageNumberOfChannels==4)
        {
	    // create a cv::Mat table (for RGBA planes)
            cv::Mat planes[] =
            {
                cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[_retinaFilter->getInputNBpixels()*2]),
                cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[_retinaFilter->getInputNBpixels()]),
                cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[0]),
                cv::Mat(inputMatToConvert.size(), dsttype)     // last channel (alpha) does not point on the valarray (not usefull in our case)
            };
            // split color cv::Mat in 4 planes... it fills valarray directely
            cv::split(cv::Mat_<Vec<T, 4> >(inputMatToConvert), planes);
        }else if (imageNumberOfChannels==3)
	{
	    // create a cv::Mat table (for RGB planes)
	    cv::Mat planes[] =
	    {
		cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[_retinaFilter->getInputNBpixels()*2]),
		cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[_retinaFilter->getInputNBpixels()]),
		cv::Mat(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[0])
	    };
	    // split color cv::Mat in 3 planes... it fills valarray directely
            cv::split(cv::Mat_<Vec<T, 3> >(inputMatToConvert), planes);
	}else if(imageNumberOfChannels==1)
	{
	    // create a cv::Mat header for the valarray
            cv::Mat dst(inputMatToConvert.size(), dsttype, &outputValarrayMatrix[0]);
	    inputMatToConvert.convertTo(dst, dsttype);
	}
        else
            CV_Error(CV_StsUnsupportedFormat, "input image must be single channel (gray levels), bgr format (color) or bgra (color with transparency which won't be considered");
	
    return imageNumberOfChannels>1; // return bool : false for gray level image processing, true for color mode
}

void Retina::clearBuffers() {_retinaFilter->clearAllBuffers();}

void Retina::activateMovingContoursProcessing(const bool activate){_retinaFilter->activateMovingContoursProcessing(activate);}

void Retina::activateContoursProcessing(const bool activate){_retinaFilter->activateContoursProcessing(activate);}

} // end of namespace cv