a wrapper class which allows the tone mapping algorithm of Meylan&al(2007) to be used with OpenCV. [詳解]
#include <retinafasttonemapping.hpp>
cv::Algorithmを継承しています。
公開メンバ関数 | |
| virtual CV_WRAP void | applyFastToneMapping (InputArray inputImage, OutputArray outputToneMappedImage)=0 |
| applies a luminance correction (initially High Dynamic Range (HDR) tone mapping) [詳解] | |
| virtual CV_WRAP 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 [詳解] | |
 基底クラス cv::Algorithm に属する継承公開メンバ関数 | |
| virtual CV_WRAP void | clear () |
| Clears the algorithm state [詳解] | |
| virtual void | write (FileStorage &fs) const |
| Stores algorithm parameters in a file storage [詳解] | |
| CV_WRAP void | write (const Ptr< FileStorage > &fs, const String &name=String()) const |
| simplified API for language bindings これはオーバーロードされたメンバ関数です。利便性のために用意されています。元の関数との違いは引き数のみです。 | |
| virtual CV_WRAP void | read (const FileNode &fn) |
| Reads algorithm parameters from a file storage [詳解] | |
| virtual CV_WRAP bool | empty () const |
| Returns true if the Algorithm is empty (e.g. in the very beginning or after unsuccessful read [詳解] | |
| virtual CV_WRAP void | save (const String &filename) const |
| virtual CV_WRAP String | getDefaultName () const |
静的公開メンバ関数 | |
| static CV_WRAP Ptr< RetinaFastToneMapping > | create (Size inputSize) |
| 基底クラス cv::Algorithm に属する継承静的公開メンバ関数 | |
| template<typename _Tp > | |
| static Ptr< _Tp > | read (const FileNode &fn) |
| Reads algorithm from the file node [詳解] | |
| template<typename _Tp > | |
| static Ptr< _Tp > | load (const String &filename, const String &objname=String()) |
| Loads algorithm from the file [詳解] | |
| template<typename _Tp > | |
| static Ptr< _Tp > | loadFromString (const String &strModel, const String &objname=String()) |
| Loads algorithm from a String [詳解] | |
その他の継承メンバ | |
| 基底クラス cv::Algorithm に属する継承限定公開メンバ関数 | |
| void | writeFormat (FileStorage &fs) const |
詳解
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.
関数詳解
◆ applyFastToneMapping()
|
pure virtual |
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
- 引数
-
inputImage the input image to process RGB or gray levels outputToneMappedImage the output tone mapped image
◆ setup()
|
pure virtual |
updates tone mapping behaviors by adjusing the local luminance computation area
- 引数
-
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)
このクラス詳解は次のファイルから抽出されました:
