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Content-Adaptive Noise Estimation for Color Images with Cross-Channel Noise Modeling
Li Dong1,2; Jiantao Zhou1,3; Yuan Yan Tang1,4
2019-03-22
Source PublicationIEEE Transactions on Image Processing
ISSN1057-7149
Volume28Issue:8Pages:4161-4176
Abstract

Noise estimation is crucial in many image processing tasks, such as denoising. Most of the existing noise estimation methods are specially developed for grayscale images. For color images, these methods simply handle each color channel independently, without considering the correlation across channels. Moreover, these methods often assume a globally fixed noise model throughout the entire image, neglecting the adaptation to the local structures. In this paper, we propose a content-Adaptive multivariate Gaussian approach to model the noise in color images, in which we explicitly consider both the content-dependence and the inter-dependence among color channels. We design an effective method for estimating the noise covariance matrices within the proposed model. Specifically, a patch selection scheme is first introduced to select the weakly textured patches via thresholding the texture strength indicators. Noticing that the patch selection actually depends on the unknown noise covariance, we present an iterative noise covariance estimation algorithm, where the patch selection and the covariance estimation are conducted alternately. For the remaining textured regions, we estimate a distinct covariance matrix associated with each pixel using a linear shrinkage estimator, which adaptively fuses the estimate coming from the weakly textured region and the sample covariance estimated from the local region. The experimental results show that our method can effectively estimate the noise covariance. The usefulness of our method is demonstrated with several image processing applications, such as color image denoising and noise-robust superpixel.

KeywordColor Image Noise Modeling Noise Estimation Weakly Textured Patch
DOI10.1109/TIP.2019.2907039
URLView the original
Indexed BySCIE
Language英語English
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Artificial Intelligence ; Engineering, Electrical & Electronic
WOS IDWOS:000473485000002
Scopus ID2-s2.0-85068178057
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Cited Times [WOS]:2   [WOS Record]     [Related Records in WOS]
Document TypeJournal article
CollectionFaculty of Science and Technology
Corresponding AuthorJiantao Zhou
Affiliation1.Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macau 999078, China
2.Department of Computer Science,Faculty of Electrical Engineering and Computer Science,Ningbo University,Ningbo,315211,China
3.State Key Laboratory of Internet of Things for Smart City,University of Macau,999078,Macao
4.Faculty of Science and Technology,UOW College Hong Kong,Community College of City University,Hong Kong,Hong Kong
First Author AffilicationFaculty of Science and Technology
Corresponding Author AffilicationFaculty of Science and Technology;  University of Macau
Recommended Citation
GB/T 7714
Li Dong,Jiantao Zhou,Yuan Yan Tang. Content-Adaptive Noise Estimation for Color Images with Cross-Channel Noise Modeling[J]. IEEE Transactions on Image Processing,2019,28(8):4161-4176.
APA Li Dong,Jiantao Zhou,&Yuan Yan Tang.(2019).Content-Adaptive Noise Estimation for Color Images with Cross-Channel Noise Modeling.IEEE Transactions on Image Processing,28(8),4161-4176.
MLA Li Dong,et al."Content-Adaptive Noise Estimation for Color Images with Cross-Channel Noise Modeling".IEEE Transactions on Image Processing 28.8(2019):4161-4176.
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