%0 Conference Proceedings
%T Image Restoration Using Anisotropic Stochastic Diffusion Collaborated with Non Local Means
%+ Faculty of Mathematics and Computer Science [Toruń]
%+ Institute of Mathematics and Physics [Bydgoszcz]
%A Borkowski, Dariusz
%A Jańczak-Borkowska, Katarzyna
%Z Part 4: Pattern Recognition and Image Processing
%< avec comité de lecture
%( Lecture Notes in Computer Science
%B 12th International Conference on Information Systems and Industrial Management (CISIM)
%C Krakow, Poland
%Y Khalid Saeed
%Y Rituparna Chaki
%Y Agostino Cortesi
%Y Sławomir Wierzchoń
%I Springer
%3 Computer Information Systems and Industrial Management
%V LNCS-8104
%P 177-189
%8 2013-09-25
%D 2013
%R 10.1007/978-3-642-40925-7_18
%K stochastic anisotropic diffusion
%K non local means
%Z Computer Science [cs]
%Z Humanities and Social Sciences/Library and information sciencesConference papers
%X In this paper we explore the problem of the reconstruction of images with additive Gaussian noise. In order to solve this inverse problem we use stochastic differential equations with reflecting boundary and famous non local means algorithm. Expressing anisotropic diffusion in terms of stochastic equations allows us to adapt the concept of similarity patches used in non local means. This novel look on the reconstruction problem is fruitful, gives encouraging results and compares favourably with other image denoising filters.
%G English
%Z TC 8
%2 https://inria.hal.science/hal-01496064/document
%2 https://inria.hal.science/hal-01496064/file/978-3-642-40925-7_18_Chapter.pdf
%L hal-01496064
%U https://inria.hal.science/hal-01496064
%~ SHS
%~ IFIP-LNCS
%~ IFIP
%~ IFIP-TC
%~ IFIP-TC8
%~ IFIP-CISIM
%~ IFIP-LNCS-8104