132 lines
5.9 KiB
Objective-C
132 lines
5.9 KiB
Objective-C
//
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// This file is auto-generated. Please don't modify it!
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//
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#pragma once
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#ifdef __cplusplus
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//#import "opencv.hpp"
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#import "opencv2/bioinspired.hpp"
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#import "opencv2/bioinspired/retinafasttonemapping.hpp"
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#else
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#define CV_EXPORTS
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#endif
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#import <Foundation/Foundation.h>
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#import "Algorithm.h"
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@class Mat;
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@class Size2i;
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NS_ASSUME_NONNULL_BEGIN
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// C++: class RetinaFastToneMapping
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/**
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* a wrapper class which allows the tone mapping algorithm of Meylan&al(2007) to be used with OpenCV.
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*
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* 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.
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* As a summary, these are the model properties:
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* - 2 stages of local luminance adaptation with a different local neighborhood for each.
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* - first stage models the retina photorecetors local luminance adaptation
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* - second stage models th ganglion cells local information adaptation
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* - compared to the initial publication, this class uses spatio-temporal low pass filters instead of spatial only filters.
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* this can help noise robustness and temporal stability for video sequence use cases.
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*
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* for more information, read to the following papers :
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* 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
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* regarding spatio-temporal filter and the bigger retina model :
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* 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.
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*
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* Member of `Bioinspired`
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*/
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CV_EXPORTS @interface RetinaFastToneMapping : Algorithm
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#ifdef __cplusplus
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@property(readonly)cv::Ptr<cv::bioinspired::RetinaFastToneMapping> nativePtrRetinaFastToneMapping;
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#endif
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#ifdef __cplusplus
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- (instancetype)initWithNativePtr:(cv::Ptr<cv::bioinspired::RetinaFastToneMapping>)nativePtr;
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+ (instancetype)fromNative:(cv::Ptr<cv::bioinspired::RetinaFastToneMapping>)nativePtr;
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#endif
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#pragma mark - Methods
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//
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// void cv::bioinspired::RetinaFastToneMapping::applyFastToneMapping(Mat inputImage, Mat& outputToneMappedImage)
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//
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/**
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* applies a luminance correction (initially High Dynamic Range (HDR) tone mapping)
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*
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* using only the 2 local adaptation stages of the retina parvocellular channel : photoreceptors
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* level and ganlion cells level. Spatio temporal filtering is applied but limited to temporal
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* smoothing and eventually high frequencies attenuation. This is a lighter method than the one
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* available using the regular retina::run method. It is then faster but it does not include
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* complete temporal filtering nor retina spectral whitening. Then, it can have a more limited
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* effect on images with a very high dynamic range. This is an adptation of the original still
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* image HDR tone mapping algorithm of David Alleyson, Sabine Susstruck and Laurence Meylan's
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* work, please cite: -> Meylan L., Alleysson D., and Susstrunk S., A Model of Retinal Local
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* Adaptation for the Tone Mapping of Color Filter Array Images, Journal of Optical Society of
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* America, A, Vol. 24, N 9, September, 1st, 2007, pp. 2807-2816
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*
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* @param inputImage the input image to process RGB or gray levels
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* @param outputToneMappedImage the output tone mapped image
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*/
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- (void)applyFastToneMapping:(Mat*)inputImage outputToneMappedImage:(Mat*)outputToneMappedImage NS_SWIFT_NAME(applyFastToneMapping(inputImage:outputToneMappedImage:));
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//
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// void cv::bioinspired::RetinaFastToneMapping::setup(float photoreceptorsNeighborhoodRadius = 3.f, float ganglioncellsNeighborhoodRadius = 1.f, float meanLuminanceModulatorK = 1.f)
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//
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/**
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* updates tone mapping behaviors by adjusing the local luminance computation area
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*
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* @param photoreceptorsNeighborhoodRadius the first stage local adaptation area
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* @param ganglioncellsNeighborhoodRadius the second stage local adaptation area
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* @param meanLuminanceModulatorK the factor applied to modulate the meanLuminance information
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* (default is 1, see reference paper)
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*/
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- (void)setup:(float)photoreceptorsNeighborhoodRadius ganglioncellsNeighborhoodRadius:(float)ganglioncellsNeighborhoodRadius meanLuminanceModulatorK:(float)meanLuminanceModulatorK NS_SWIFT_NAME(setup(photoreceptorsNeighborhoodRadius:ganglioncellsNeighborhoodRadius:meanLuminanceModulatorK:));
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/**
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* updates tone mapping behaviors by adjusing the local luminance computation area
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*
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* @param photoreceptorsNeighborhoodRadius the first stage local adaptation area
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* @param ganglioncellsNeighborhoodRadius the second stage local adaptation area
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* (default is 1, see reference paper)
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*/
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- (void)setup:(float)photoreceptorsNeighborhoodRadius ganglioncellsNeighborhoodRadius:(float)ganglioncellsNeighborhoodRadius NS_SWIFT_NAME(setup(photoreceptorsNeighborhoodRadius:ganglioncellsNeighborhoodRadius:));
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/**
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* updates tone mapping behaviors by adjusing the local luminance computation area
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*
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* @param photoreceptorsNeighborhoodRadius the first stage local adaptation area
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* (default is 1, see reference paper)
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*/
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- (void)setup:(float)photoreceptorsNeighborhoodRadius NS_SWIFT_NAME(setup(photoreceptorsNeighborhoodRadius:));
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/**
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* updates tone mapping behaviors by adjusing the local luminance computation area
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*
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* (default is 1, see reference paper)
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*/
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- (void)setup NS_SWIFT_NAME(setup());
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//
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// static Ptr_RetinaFastToneMapping cv::bioinspired::RetinaFastToneMapping::create(Size inputSize)
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//
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+ (RetinaFastToneMapping*)create:(Size2i*)inputSize NS_SWIFT_NAME(create(inputSize:));
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@end
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NS_ASSUME_NONNULL_END
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