a wrapper class which allows the tone mapping algorithm of Meylan&al(2007) to be used with OpenCV.  
 More...
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| virtual void  | applyFastToneMapping (InputArray inputImage, OutputArray outputToneMappedImage)=0 | 
|   | applies a luminance correction (initially High Dynamic Range (HDR) tone mapping)  
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| virtual void  | setup (const float photoreceptorsNeighborhoodRadius=3.f, const float ganglioncellsNeighborhoodRadius=1.f, const float meanLuminanceModulatorK=1.f)=0 | 
|   | updates tone mapping behaviors by adjusing the local luminance computation area  
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|   | Algorithm () | 
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| virtual  | ~Algorithm () | 
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| virtual void  | clear () | 
|   | Clears the algorithm state.  
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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.  
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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.  
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| virtual void  | save (const String &filename) const | 
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| virtual void  | write (FileStorage &fs) const | 
|   | Stores algorithm parameters in a file storage.  
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| void  | write (FileStorage &fs, const String &name) const | 
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a wrapper class which allows the tone mapping algorithm of Meylan&al(2007) to be used with OpenCV. 
This algorithm is already implemented in thre Retina class (retina::applyFastToneMapping) but used it does not require all the retina model to be allocated. This allows a light memory use for low memory devices (smartphones, etc. As a summary, these are the model properties:
- 2 stages of local luminance adaptation with a different local neighborhood for each.
 
- first stage models the retina photorecetors local luminance adaptation
 
- second stage models th ganglion cells local information adaptation
 
- compared to the initial publication, this class uses spatio-temporal low pass filters instead of spatial only filters. this can help noise robustness and temporal stability for video sequence use cases.
 
for more information, read to the following papers : Meylan L., Alleysson D., and Susstrunk S., A Model of Retinal Local Adaptation for the Tone Mapping of Color Filter Array Images, Journal of Optical Society of America, A, Vol. 24, N 9, September, 1st, 2007, pp. 2807-2816Benoit 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 regarding spatio-temporal filter and the bigger retina model : 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. 
 
  
  
      
        
          | virtual void cv::bioinspired::RetinaFastToneMapping::applyFastToneMapping  | 
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          InputArray |           inputImage,  | 
         
        
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          OutputArray |           outputToneMappedImage ) | 
         
       
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pure virtual   | 
  
| Python: | 
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 | cv.bioinspired.RetinaFastToneMapping.applyFastToneMapping( | inputImage[, outputToneMappedImage] | ) ->  | outputToneMappedImage | 
 
applies a luminance correction (initially High Dynamic Range (HDR) tone mapping) 
using only the 2 local adaptation stages of the retina parvocellular channel : photoreceptors level and ganlion cells level. Spatio temporal filtering is applied but limited to temporal smoothing and eventually high frequencies attenuation. This is a lighter method than the one available using the regular retina::run method. It is then faster but it does not include complete temporal filtering nor retina spectral whitening. Then, it can have a more limited effect on images with a very high dynamic range. This is an adptation of the original still image HDR tone mapping algorithm of David Alleyson, Sabine Susstruck and Laurence Meylan's work, please cite: -> Meylan L., Alleysson D., and Susstrunk S., A Model of Retinal Local Adaptation for the Tone Mapping of Color Filter Array Images, Journal of Optical Society of America, A, Vol. 24, N 9, September, 1st, 2007, pp. 2807-2816
- Parameters
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    | inputImage | the input image to process RGB or gray levels  | 
    | outputToneMappedImage | the output tone mapped image  |