[−][src]Trait opencv::bioinspired::RetinaFastToneMapping

pub trait RetinaFastToneMapping: AlgorithmTrait {
    pub fn as_raw_RetinaFastToneMapping(&self) -> *const c_void;

    pub fn as_raw_mut_RetinaFastToneMapping(&mut self) -> *mut c_void;

    pub fn apply_fast_tone_mapping(
        &mut self, 
        input_image: &dyn ToInputArray, 
        output_tone_mapped_image: &mut dyn ToOutputArray
    ) -> Result<()> { ... }

    pub fn setup(
        &mut self, 
        photoreceptors_neighborhood_radius: f32, 
        ganglioncells_neighborhood_radius: f32, 
        mean_luminance_modulator_k: f32
    ) -> Result<()> { ... }
}

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

pub fn as_raw_RetinaFastToneMapping(&self) -> *const c_void[src]

pub fn as_raw_mut_RetinaFastToneMapping(&mut self) -> *mut c_void[src]

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Provided methods

pub fn apply_fast_tone_mapping(
    &mut self,
    input_image: &dyn ToInputArray,
    output_tone_mapped_image: &mut dyn ToOutputArray
) -> Result<()>[src]

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

  • inputImage: the input image to process RGB or gray levels
  • outputToneMappedImage: the output tone mapped image

pub fn setup(
    &mut self,
    photoreceptors_neighborhood_radius: f32,
    ganglioncells_neighborhood_radius: f32,
    mean_luminance_modulator_k: f32
) -> Result<()>[src]

updates tone mapping behaviors by adjusing the local luminance computation area

Parameters

  • photoreceptorsNeighborhoodRadius: the first stage local adaptation area
  • ganglioncellsNeighborhoodRadius: the second stage local adaptation area
  • meanLuminanceModulatorK: the factor applied to modulate the meanLuminance information (default is 1, see reference paper)

C++ default parameters

  • photoreceptors_neighborhood_radius: 3.f
  • ganglioncells_neighborhood_radius: 1.f
  • mean_luminance_modulator_k: 1.f
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Implementations

impl<'_> dyn RetinaFastToneMapping + '_[src]

pub fn create(input_size: Size) -> Result<Ptr<dyn RetinaFastToneMapping>>[src]

Implementors

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