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Commit 1a749c51 authored by Alexandre Benoit's avatar Alexandre Benoit
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optimised input image management

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modules/contrib/include/opencv2/contrib/retina.hpp
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...@@ -77,146 +77,167 @@ ...@@ -77,146 +77,167 @@
namespace cv namespace cv
{ {
enum RETINA_COLORSAMPLINGMETHOD enum RETINA_COLORSAMPLINGMETHOD
{ {
RETINA_COLOR_RANDOM, /// each pixel position is either R, G or B in a random choice RETINA_COLOR_RANDOM, /// each pixel position is either R, G or B in a random choice
RETINA_COLOR_DIAGONAL,/// color sampling is RGBRGBRGB..., line 2 BRGBRGBRG..., line 3, GBRGBRGBR... RETINA_COLOR_DIAGONAL,/// color sampling is RGBRGBRGB..., line 2 BRGBRGBRG..., line 3, GBRGBRGBR...
RETINA_COLOR_BAYER/// standard bayer sampling RETINA_COLOR_BAYER/// standard bayer sampling
}; };
class RetinaFilter; class RetinaFilter;
/** /**
* @brief a wrapper class which allows the use of the Gipsa/Listic Labs retina model * @brief a wrapper class which allows the use of the Gipsa/Listic Labs retina model
* @class Retina object is a wrapper class which allows the Gipsa/Listic Labs model to be used. * @class Retina object is a wrapper class which allows the Gipsa/Listic Labs model to be used.
* This retina model allows spatio-temporal image processing (applied on still images, video sequences). * This retina model allows spatio-temporal image processing (applied on still images, video sequences).
* As a summary, these are the retina model properties: * As a summary, these are the retina model properties:
* => It applies a spectral whithening (mid-frequency details enhancement) * => It applies a spectral whithening (mid-frequency details enhancement)
* => high frequency spatio-temporal noise reduction * => high frequency spatio-temporal noise reduction
* => low frequency luminance to be reduced (luminance range compression) * => low frequency luminance to be reduced (luminance range compression)
* => local logarithmic luminance compression allows details to be enhanced in low light conditions * => local logarithmic luminance compression allows details to be enhanced in low light conditions
* *
* for more information, reer to the following papers : * for more information, reer to the following papers :
* 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 * 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
* 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. * 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.
*/ */
class CV_EXPORTS Retina { class CV_EXPORTS Retina {
public: public:
/** /**
* Main constructor with most commun use setup : create an instance of color ready retina model * Main constructor with most commun use setup : create an instance of color ready retina model
* @param inputSize : the input frame size * @param inputSize : the input frame size
*/ */
Retina(const std::string parametersSaveFile, Size inputSize); Retina(const std::string parametersSaveFile, Size inputSize);
/** /**
* Complete Retina filter constructor which allows all basic structural parameters definition * Complete Retina filter constructor which allows all basic structural parameters definition
* @param inputSize : the input frame size * @param inputSize : the input frame size
* @param colorMode : the chosen processing mode : with or without color processing * @param colorMode : the chosen processing mode : with or without color processing
* @param samplingMethod: specifies which kind of color sampling will be used * @param samplingMethod: specifies which kind of color sampling will be used
* @param useRetinaLogSampling: activate retina log sampling, if true, the 2 following parameters can be used * @param useRetinaLogSampling: activate retina log sampling, if true, the 2 following parameters can be used
* @param reductionFactor: only usefull if param useRetinaLogSampling=true, specifies the reduction factor of the output frame (as the center (fovea) is high resolution and corners can be underscaled, then a reduction of the output is allowed without precision leak * @param reductionFactor: only usefull if param useRetinaLogSampling=true, specifies the reduction factor of the output frame (as the center (fovea) is high resolution and corners can be underscaled, then a reduction of the output is allowed without precision leak
* @param samplingStrenght: only usefull if param useRetinaLogSampling=true, specifies the strenght of the log scale that is applied * @param samplingStrenght: only usefull if param useRetinaLogSampling=true, specifies the strenght of the log scale that is applied
*/ */
Retina(const std::string parametersSaveFile, Size inputSize, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod=RETINA_COLOR_BAYER, const bool useRetinaLogSampling=false, const double reductionFactor=1.0, const double samplingStrenght=10.0); Retina(const std::string parametersSaveFile, Size inputSize, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod=RETINA_COLOR_BAYER, const bool useRetinaLogSampling=false, const double reductionFactor=1.0, const double samplingStrenght=10.0);
virtual ~Retina(); virtual ~Retina();
/** /**
* try to open an XML retina parameters file to adjust current retina instance setup * try to open an XML retina parameters file to adjust current retina instance setup
* => if the xml file does not exist, then default setup is applied * => if the xml file does not exist, then default setup is applied
* => warning, Exceptions are thrown if read XML file is not valid * => warning, Exceptions are thrown if read XML file is not valid
* @param retinaParameterFile : the parameters filename * @param retinaParameterFile : the parameters filename
*/ */
void setup(std::string retinaParameterFile="", const bool applyDefaultSetupOnFailure=true); void setup(std::string retinaParameterFile="", const bool applyDefaultSetupOnFailure=true);
/** /**
* parameters setup display method * parameters setup display method
* @return a string which contains formatted parameters information * @return a string which contains formatted parameters information
*/ */
const std::string printSetup(); const std::string printSetup();
/** /**
* setup the OPL and IPL parvo channels (see biologocal model) * setup the OPL and IPL parvo channels (see biologocal model)
* OPL is referred as Outer Plexiform Layer of the retina, it allows the spatio-temporal filtering which withens the spectrum and reduces spatio-temporal noise while attenuating global luminance (low frequency energy) * OPL is referred as Outer Plexiform Layer of the retina, it allows the spatio-temporal filtering which withens the spectrum and reduces spatio-temporal noise while attenuating global luminance (low frequency energy)
* IPL parvo is the OPL next processing stage, it refers to Inner Plexiform layer of the retina, it allows high contours sensitivity in foveal vision. * IPL parvo is the OPL next processing stage, it refers to Inner Plexiform layer of the retina, it allows high contours sensitivity in foveal vision.
* for more informations, please have a look at the paper 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 * for more informations, please have a look at the paper 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
* @param colorMode : specifies if (true) color is processed of not (false) to then processing gray level image * @param colorMode : specifies if (true) color is processed of not (false) to then processing gray level image
* @param normaliseOutput : specifies if (true) output is rescaled between 0 and 255 of not (false) * @param normaliseOutput : specifies if (true) output is rescaled between 0 and 255 of not (false)
* @param photoreceptorsLocalAdaptationSensitivity: the photoreceptors sensitivity renage is 0-1 (more log compression effect when value increases) * @param photoreceptorsLocalAdaptationSensitivity: the photoreceptors sensitivity renage is 0-1 (more log compression effect when value increases)
* @param photoreceptorsTemporalConstant: the time constant of the first order low pass filter of the photoreceptors, use it to cut high temporal frequencies (noise or fast motion), unit is frames, typical value is 1 frame * @param photoreceptorsTemporalConstant: the time constant of the first order low pass filter of the photoreceptors, use it to cut high temporal frequencies (noise or fast motion), unit is frames, typical value is 1 frame
* @param photoreceptorsSpatialConstant: the spatial constant of the first order low pass filter of the photoreceptors, use it to cut high spatial frequencies (noise or thick contours), unit is pixels, typical value is 1 pixel * @param photoreceptorsSpatialConstant: the spatial constant of the first order low pass filter of the photoreceptors, use it to cut high spatial frequencies (noise or thick contours), unit is pixels, typical value is 1 pixel
* @param horizontalCellsGain: gain of the horizontal cells network, if 0, then the mean value of the output is zero, if the parameter is near 1, then, the luminance is not filtered and is still reachable at the output, typicall value is 0 * @param horizontalCellsGain: gain of the horizontal cells network, if 0, then the mean value of the output is zero, if the parameter is near 1, then, the luminance is not filtered and is still reachable at the output, typicall value is 0
* @param HcellsTemporalConstant: the time constant of the first order low pass filter of the horizontal cells, use it to cut low temporal frequencies (local luminance variations), unit is frames, typical value is 1 frame, as the photoreceptors * @param HcellsTemporalConstant: the time constant of the first order low pass filter of the horizontal cells, use it to cut low temporal frequencies (local luminance variations), unit is frames, typical value is 1 frame, as the photoreceptors
* @param HcellsSpatialConstant: the spatial constant of the first order low pass filter of the horizontal cells, use it to cut low spatial frequencies (local luminance), unit is pixels, typical value is 5 pixel, this value is also used for local contrast computing when computing the local contrast adaptation at the ganglion cells level (Inner Plexiform Layer parvocellular channel model) * @param HcellsSpatialConstant: the spatial constant of the first order low pass filter of the horizontal cells, use it to cut low spatial frequencies (local luminance), unit is pixels, typical value is 5 pixel, this value is also used for local contrast computing when computing the local contrast adaptation at the ganglion cells level (Inner Plexiform Layer parvocellular channel model)
* @param ganglionCellsSensitivity: the compression strengh of the ganglion cells local adaptation output, set a value between 160 and 250 for best results, a high value increases more the low value sensitivity... and the output saturates faster, recommended value: 230 * @param ganglionCellsSensitivity: the compression strengh of the ganglion cells local adaptation output, set a value between 160 and 250 for best results, a high value increases more the low value sensitivity... and the output saturates faster, recommended value: 230
*/ */
void setupOPLandIPLParvoChannel(const bool colorMode=true, const bool normaliseOutput = true, const double photoreceptorsLocalAdaptationSensitivity=0.7, const double photoreceptorsTemporalConstant=0.5, const double photoreceptorsSpatialConstant=0.53, const double horizontalCellsGain=0, const double HcellsTemporalConstant=1, const double HcellsSpatialConstant=7, const double ganglionCellsSensitivity=0.7); void setupOPLandIPLParvoChannel(const bool colorMode=true, const bool normaliseOutput = true, const double photoreceptorsLocalAdaptationSensitivity=0.7, const double photoreceptorsTemporalConstant=0.5, const double photoreceptorsSpatialConstant=0.53, const double horizontalCellsGain=0, const double HcellsTemporalConstant=1, const double HcellsSpatialConstant=7, const double ganglionCellsSensitivity=0.7);
/** /**
* set parameters values for the Inner Plexiform Layer (IPL) magnocellular channel * set parameters values for the Inner Plexiform Layer (IPL) magnocellular channel
* this channel processes signals outpint from OPL processing stage in peripheral vision, it allows motion information enhancement. It is decorrelated from the details channel. See reference paper for more details. * this channel processes signals outpint from OPL processing stage in peripheral vision, it allows motion information enhancement. It is decorrelated from the details channel. See reference paper for more details.
* @param normaliseOutput : specifies if (true) output is rescaled between 0 and 255 of not (false) * @param normaliseOutput : specifies if (true) output is rescaled between 0 and 255 of not (false)
* @param parasolCells_beta: the low pass filter gain used for local contrast adaptation at the IPL level of the retina (for ganglion cells local adaptation), typical value is 0 * @param parasolCells_beta: the low pass filter gain used for local contrast adaptation at the IPL level of the retina (for ganglion cells local adaptation), typical value is 0
* @param parasolCells_tau: the low pass filter time constant used for local contrast adaptation at the IPL level of the retina (for ganglion cells local adaptation), unit is frame, typical value is 0 (immediate response) * @param parasolCells_tau: the low pass filter time constant used for local contrast adaptation at the IPL level of the retina (for ganglion cells local adaptation), unit is frame, typical value is 0 (immediate response)
* @param parasolCells_k: the low pass filter spatial constant used for local contrast adaptation at the IPL level of the retina (for ganglion cells local adaptation), unit is pixels, typical value is 5 * @param parasolCells_k: the low pass filter spatial constant used for local contrast adaptation at the IPL level of the retina (for ganglion cells local adaptation), unit is pixels, typical value is 5
* @param amacrinCellsTemporalCutFrequency: the time constant of the first order high pass fiter of the magnocellular way (motion information channel), unit is frames, tipicall value is 5 * @param amacrinCellsTemporalCutFrequency: the time constant of the first order high pass fiter of the magnocellular way (motion information channel), unit is frames, tipicall value is 5
* @param V0CompressionParameter: the compression strengh of the ganglion cells local adaptation output, set a value between 160 and 250 for best results, a high value increases more the low value sensitivity... and the output saturates faster, recommended value: 200 * @param V0CompressionParameter: the compression strengh of the ganglion cells local adaptation output, set a value between 160 and 250 for best results, a high value increases more the low value sensitivity... and the output saturates faster, recommended value: 200
* @param localAdaptintegration_tau: specifies the temporal constant of the low pas filter involved in the computation of the local "motion mean" for the local adaptation computation * @param localAdaptintegration_tau: specifies the temporal constant of the low pas filter involved in the computation of the local "motion mean" for the local adaptation computation
* @param localAdaptintegration_k: specifies the spatial constant of the low pas filter involved in the computation of the local "motion mean" for the local adaptation computation * @param localAdaptintegration_k: specifies the spatial constant of the low pas filter involved in the computation of the local "motion mean" for the local adaptation computation
*/ */
void setupIPLMagnoChannel(const bool normaliseOutput = true, const double parasolCells_beta=0, const double parasolCells_tau=0, const double parasolCells_k=7, const double amacrinCellsTemporalCutFrequency=1.2, const double V0CompressionParameter=0.95, const double localAdaptintegration_tau=0, const double localAdaptintegration_k=7); void setupIPLMagnoChannel(const bool normaliseOutput = true, const double parasolCells_beta=0, const double parasolCells_tau=0, const double parasolCells_k=7, const double amacrinCellsTemporalCutFrequency=1.2, const double V0CompressionParameter=0.95, const double localAdaptintegration_tau=0, const double localAdaptintegration_k=7);
/**
* method which allows retina to be applied on an input image /**
* @param * method which allows retina to be applied on an input image
* /// encapsulated retina module is ready to deliver its outputs using dedicated acccessors, see getParvo and getMagno methods * @param
* * /// encapsulated retina module is ready to deliver its outputs using dedicated acccessors, see getParvo and getMagno methods
*/ *
void run(const Mat &inputImage); */
/** void run(const Mat &inputImage);
* accessor of the details channel of the retina (models foveal vision)
* @param retinaOutput_parvo : the output buffer (reallocated if necessary) /**
*/ * accessor of the details channel of the retina (models foveal vision)
void getParvo(Mat &retinaOutput_parvo); * @param retinaOutput_parvo : the output buffer (reallocated if necessary)
*/
/** void getParvo(Mat &retinaOutput_parvo);
* accessor of the motion channel of the retina (models peripheral vision)
* @param retinaOutput_magno : the output buffer (reallocated if necessary) /**
*/ * accessor of the motion channel of the retina (models peripheral vision)
void getMagno(Mat &retinaOutput_magno); * @param retinaOutput_magno : the output buffer (reallocated if necessary)
*/
void clearBuffers(); void getMagno(Mat &retinaOutput_magno);
protected: /**
//// Parameteres setup members * activate color saturation as the final step of the color demultiplexing process
// parameters file ... saved on instance delete * -> this saturation is a sigmoide function applied to each channel of the demultiplexed image.
FileStorage _parametersSaveFile; * @param saturateColors: boolean that activates color saturation (if true) or desactivate (if false)
std::string _parametersSaveFileName; * @param colorSaturationValue: the saturation factor
//// Retina model related modules */
// buffer that ensure library cross-compatibility void setColorSaturation(const bool saturateColors=true, const double colorSaturationValue=4.0);
std::valarray<double> _inputBuffer;
/**
// pointer to retina model * clear all retina buffers (equivalent to opening the eyes after a long period of eye close ;o)
RetinaFilter* _retinaFilter; */
void clearBuffers();
/**
* exports a valarray buffer outing from HVStools objects to a cv::Mat in CV_8UC1 (gray level picture) or CV_8UC3 (color) format protected:
* @param grayMatrixToConvert the valarray to export to OpenCV //// Parameteres setup members
* @param nbRows : the number of rows of the valarray flatten matrix // parameters file ... saved on instance delete
* @param nbColumns : the number of rows of the valarray flatten matrix FileStorage _parametersSaveFile;
* @param colorMode : a flag which mentions if matrix is color (true) or graylevel (false) std::string _parametersSaveFileName;
* @param outBuffer : the output matrix which is reallocated to satisfy Retina output buffer dimensions //// Retina model related modules
*/ // buffer that ensure library cross-compatibility
void _convertValarrayGrayBuffer2cvMat(const std::valarray<double> &grayMatrixToConvert, const unsigned int nbRows, const unsigned int nbColumns, const bool colorMode, Mat &outBuffer); std::valarray<double> _inputBuffer;
// private method called by constructirs // pointer to retina model
void _init(const std::string parametersSaveFile, Size inputSize, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod=RETINA_COLOR_BAYER, const bool useRetinaLogSampling=false, const double reductionFactor=1.0, const double samplingStrenght=10.0); RetinaFilter* _retinaFilter;
/**
}; * exports a valarray buffer outing from HVStools objects to a cv::Mat in CV_8UC1 (gray level picture) or CV_8UC3 (color) format
* @param grayMatrixToConvert the valarray to export to OpenCV
* @param nbRows : the number of rows of the valarray flatten matrix
* @param nbColumns : the number of rows of the valarray flatten matrix
* @param colorMode : a flag which mentions if matrix is color (true) or graylevel (false)
* @param outBuffer : the output matrix which is reallocated to satisfy Retina output buffer dimensions
*/
void _convertValarrayBuffer2cvMat(const std::valarray<double> &grayMatrixToConvert, const unsigned int nbRows, const unsigned int nbColumns, const bool colorMode, Mat &outBuffer);
/**
*
* @param inputMatToConvert : the OpenCV cv::Mat that has to be converted to gray or RGB valarray buffer that will be processed by the retina model
* @param outputValarrayMatrix : the output valarray
* @return the input image color mode (color=true, gray levels=false)
*/
const bool _convertCvMat2ValarrayBuffer(const cv::Mat inputMatToConvert, std::valarray<double> &outputValarrayMatrix);
// private method called by constructirs
void _init(const std::string parametersSaveFile, Size inputSize, const bool colorMode, RETINA_COLORSAMPLINGMETHOD colorSamplingMethod=RETINA_COLOR_BAYER, const bool useRetinaLogSampling=false, const double reductionFactor=1.0, const double samplingStrenght=10.0);
};
} }
#endif /* __OPENCV_CONTRIB_RETINA_HPP__ */ #endif /* __OPENCV_CONTRIB_RETINA_HPP__ */
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