General Adaptive Neighborhood Image Processing (GANIP)
| Autor: | Debayle, Johan |
|---|---|
| Přispěvatelé: | École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT), Université de Lyon, Centre National de la Recherche Scientifique (CNRS), Laboratoire Georges Friedel (LGF-ENSMSE), Université de Lyon-Centre National de la Recherche Scientifique (CNRS)-École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT), Centre Sciences des Processus Industriels et Naturels (SPIN-ENSMSE), Département Procédés de Mise en oeuvre des Milieux Granulaires (PMMG-ENSMSE), Institut Mines-Télécom [Paris] (IMT)-Institut Mines-Télécom [Paris] (IMT)-École des Mines de Saint-Étienne (Mines Saint-Étienne MSE), Society for Imaging Sciences and Technology, Lillouch, Fatima |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
[SPI.GPROC] Engineering Sciences [physics]/Chemical and Process Engineering
[INFO.INFO-TS] Computer Science [cs]/Signal and Image Processing ComputingMethodologies_IMAGEPROCESSINGANDCOMPUTERVISION [INFO.INFO-CV]Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] Logarithmic image processing [INFO.INFO-MO]Computer Science [cs]/Modeling and Simulation Adaptive image processing [INFO.INFO-CV] Computer Science [cs]/Computer Vision and Pattern Recognition [cs.CV] [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing Image enhancement Image denoising [SPI.GPROC]Engineering Sciences [physics]/Chemical and Process Engineering [INFO.INFO-MO] Computer Science [cs]/Modeling and Simulation Local image representation Non-linear image filtering |
| Zdroj: | 2019 IS&T International Symposium on Electronic Imaging (IE2019)-Image Processing: Algorithms and Systems XVII 2019 IS&T International Symposium on Electronic Imaging (IE2019)-Image Processing: Algorithms and Systems XVII, Society for Imaging Sciences and Technology, Jan 2019, Burlingame, United States |
| Popis: | Conférence invitée de Johan Debayle, centre SPIN, LGF UMR CNRS 5307, en qualité de “Invited Talk“.; International audience; The framework entitled General Adaptive Neighborhood Image Processing (GANIP) has been introduced in order to propose an original local image representation and mathematical structure for adaptive non-linear processing and analysis of gray-tone images. In this talk, the GANIP framework is first presented and particularly studied in the context of image filtering. The central idea is based on the key notion of adaptivity which is simultaneously associated with the analyzing scales, the spatial structures and the intensity values of the image to be addressed. Several adaptive image transforms are then defined in the context of convolution analysis, order filtering or mathematical morphology. Such operators are no longer spatially invariant, but vary over the whole image with General Adaptive Neighborhoods (GANs) as adaptive operational windows, taking intrinsically into account the local image features. The GANIP framework allows efficient adaptive image filters to be built and opens new pathways that promise large prospects for non-linear image filtering. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|