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On modeling interchannel dependency for color image denoising
Author(s) -
Li Xin
Publication year - 2007
Publication title -
international journal of imaging systems and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.359
H-Index - 47
eISSN - 1098-1098
pISSN - 0899-9457
DOI - 10.1002/ima.20112
Subject(s) - computer science , dependency (uml) , artificial intelligence , fuse (electrical) , chromatic adaptation , noise reduction , pattern recognition (psychology) , computer vision , invariant (physics) , noise (video) , image denoising , image (mathematics) , mathematics , engineering , electrical engineering , mathematical physics
In this article, we study the modeling of interchannel dependency and its application into removing additive noise from corrupted color images. We start from an ad hoc spatially invariant linear interpolative model for characterizing color‐difference and demonstrate how it can be jointly used with a variational intrachannel dependency model to suppress noise by alternating projections. Then we present two nonlinear diffusion‐based models in the color‐difference domain and suggest their spatial adaptation property better matches the class of images with strong chromatic edges. The diversity of interchannel dependency models also motivates us to fuse multiple denoised images from different models to obtain better denoised results. Experimental results are reported to justify the importance of matching the hypothesized dependency model with observation data as well as the benefit of multihypothesis fusion. © 2007 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 17, 163–173, 2007