Trait opencv::hub_prelude::RetinaFastToneMappingConst[−][src]

pub trait RetinaFastToneMappingConst: AlgorithmTraitConst {
    fn as_raw_RetinaFastToneMapping(&self) -> *const c_void;
}
Expand description

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.

Required methods

Implementors