Trait opencv::prelude::RetinaConst
source · [−]pub trait RetinaConst: AlgorithmTraitConst {
fn as_raw_Retina(&self) -> *const c_void;
fn write(&self, fs: &str) -> Result<()> { ... }
fn write_to_storage(&self, fs: &mut FileStorage) -> Result<()> { ... }
fn get_magno_raw(&self) -> Result<Mat> { ... }
fn get_parvo_raw(&self) -> Result<Mat> { ... }
}
Expand description
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.
Required Methods
fn as_raw_Retina(&self) -> *const c_void
Provided Methods
sourcefn write(&self, fs: &str) -> Result<()>
fn write(&self, fs: &str) -> Result<()>
Write xml/yml formated parameters information
Parameters
- fs: the filename of the xml file that will be open and writen with formatted parameters information
sourcefn write_to_storage(&self, fs: &mut FileStorage) -> Result<()>
fn write_to_storage(&self, fs: &mut FileStorage) -> Result<()>
Write xml/yml formated parameters information
Parameters
- fs: the filename of the xml file that will be open and writen with formatted parameters information
Overloaded parameters
sourcefn get_magno_raw(&self) -> Result<Mat>
fn get_magno_raw(&self) -> Result<Mat>
Accessor of the motion channel of the retina (models peripheral vision).
See also
getMagno
Overloaded parameters
sourcefn get_parvo_raw(&self) -> Result<Mat>
fn get_parvo_raw(&self) -> Result<Mat>
Accessor of the details channel of the retina (models foveal vision).
See also
getParvo