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virtual void | activateContoursProcessing (const bool activate)=0 |
| Activate/desactivate the Parvocellular pathway processing (contours information extraction), by default, it is activated. More...
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virtual void | activateMovingContoursProcessing (const bool activate)=0 |
| Activate/desactivate the Magnocellular pathway processing (motion information extraction), by default, it is activated. More...
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virtual void | applyFastToneMapping (InputArray inputImage, OutputArray outputToneMappedImage)=0 |
| Method which processes an image in the aim to correct its luminance correct backlight problems, enhance details in shadows. More...
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virtual void | clearBuffers ()=0 |
| Clears all retina buffers. More...
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virtual Size | getInputSize ()=0 |
| Retreive retina input buffer size. More...
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virtual void | getMagno (OutputArray retinaOutput_magno)=0 |
| Accessor of the motion channel of the retina (models peripheral vision). More...
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virtual void | getMagnoRAW (OutputArray retinaOutput_magno)=0 |
| Accessor of the motion channel of the retina (models peripheral vision). More...
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virtual const Mat | getMagnoRAW () const =0 |
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virtual Size | getOutputSize ()=0 |
| Retreive retina output buffer size that can be different from the input if a spatial log transformation is applied. More...
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virtual RetinaParameters | getParameters ()=0 |
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virtual void | getParvo (OutputArray retinaOutput_parvo)=0 |
| Accessor of the details channel of the retina (models foveal vision). More...
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virtual void | getParvoRAW (OutputArray retinaOutput_parvo)=0 |
| Accessor of the details channel of the retina (models foveal vision). More...
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virtual const Mat | getParvoRAW () const =0 |
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virtual const String | printSetup ()=0 |
| Outputs a string showing the used parameters setup. More...
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virtual void | run (InputArray inputImage)=0 |
| Method which allows retina to be applied on an input image,. More...
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virtual void | setColorSaturation (const bool saturateColors=true, const float colorSaturationValue=4.0f)=0 |
| Activate color saturation as the final step of the color demultiplexing process -> this saturation is a sigmoide function applied to each channel of the demultiplexed image. More...
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virtual void | setup (String retinaParameterFile="", const bool applyDefaultSetupOnFailure=true)=0 |
| Try to open an XML retina parameters file to adjust current retina instance setup. More...
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virtual void | setup (cv::FileStorage &fs, const bool applyDefaultSetupOnFailure=true)=0 |
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virtual void | setup (RetinaParameters newParameters)=0 |
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virtual void | setupIPLMagnoChannel (const bool normaliseOutput=true, const float parasolCells_beta=0.f, const float parasolCells_tau=0.f, const float parasolCells_k=7.f, const float amacrinCellsTemporalCutFrequency=1.2f, const float V0CompressionParameter=0.95f, const float localAdaptintegration_tau=0.f, const float localAdaptintegration_k=7.f)=0 |
| Set parameters values for the Inner Plexiform Layer (IPL) magnocellular channel. More...
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virtual void | setupOPLandIPLParvoChannel (const bool colorMode=true, const bool normaliseOutput=true, const float photoreceptorsLocalAdaptationSensitivity=0.7f, const float photoreceptorsTemporalConstant=0.5f, const float photoreceptorsSpatialConstant=0.53f, const float horizontalCellsGain=0.f, const float HcellsTemporalConstant=1.f, const float HcellsSpatialConstant=7.f, const float ganglionCellsSensitivity=0.7f)=0 |
| Setup the OPL and IPL parvo channels (see biologocal model) More...
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virtual void | write (String fs) const =0 |
| Write xml/yml formated parameters information. More...
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virtual void | write (FileStorage &fs) const =0 |
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| Algorithm () |
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virtual | ~Algorithm () |
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virtual void | clear () |
| Clears the algorithm state. More...
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virtual bool | empty () const |
| Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read. More...
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virtual String | getDefaultName () const |
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virtual void | read (const FileNode &fn) |
| Reads algorithm parameters from a file storage. More...
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virtual void | save (const String &filename) const |
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class which allows the Gipsa/Listic Labs model to be used with OpenCV.
This retina model allows spatio-temporal image processing (applied on still images, video sequences). As a summary, these are the retina model properties:
- It applies a spectral whithening (mid-frequency details enhancement)
- high frequency spatio-temporal noise reduction
- low frequency luminance to be reduced (luminance range compression)
- local logarithmic luminance compression allows details to be enhanced in low light conditions
USE : this model can be used basically for spatio-temporal video effects but also for : _using the getParvo method output matrix : texture analysiswith enhanced signal to noise ratio and enhanced details robust against input images luminance ranges _using the getMagno method output matrix : motion analysis also with the previously cited properties
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 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.
virtual void cv::bioinspired::Retina::setupOPLandIPLParvoChannel |
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const bool |
colorMode = true , |
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const bool |
normaliseOutput = true , |
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const float |
photoreceptorsLocalAdaptationSensitivity = 0.7f , |
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const float |
photoreceptorsTemporalConstant = 0.5f , |
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const float |
photoreceptorsSpatialConstant = 0.53f , |
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const float |
horizontalCellsGain = 0.f , |
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const float |
HcellsTemporalConstant = 1.f , |
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const float |
HcellsSpatialConstant = 7.f , |
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const float |
ganglionCellsSensitivity = 0.7f |
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pure virtual |
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) IPL parvo is the OPL next processing stage, it refers to a part of the Inner Plexiform layer of the retina, it allows high contours sensitivity in foveal vision. See reference papers for more informations. 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
- Parameters
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colorMode | specifies if (true) color is processed of not (false) to then processing gray level image |
normaliseOutput | specifies if (true) output is rescaled between 0 and 255 of not (false) |
photoreceptorsLocalAdaptationSensitivity | the photoreceptors sensitivity renage is 0-1 (more log compression effect when value increases) |
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 |
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 |
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 |
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 |
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) |
ganglionCellsSensitivity | the compression strengh of the ganglion cells local adaptation output, set a value between 0.6 and 1 for best results, a high value increases more the low value sensitivity... and the output saturates faster, recommended value: 0.7 |