NDLI: Restoration of noisy regions modeled by noncausal Markov random fields of unknown parameters

Content Provider	IEEE Xplore Digital Library
Author	Waks, A. Tretiak, O.J. Gregoriou, G.K.
Copyright Year	1990
Description	Author affiliation: Image Process. Center, Drexel Univ., Philadelphia, PA, USA (Waks, A.; Tretiak, O.J.; Gregoriou, G.K.)
Abstract	The problem of restoring noisy images when the model parameters are not known is discussed. The underlying field, x, is modeled as a noncausal Markov random field (MRF), namely, either a multilevel logistic (MLL) or a Gaussian MRF, and is corrupted by additive independently identically distributed (i.i.d.) Gaussian noise. The application is a restoration/segmentation of regions of interest in an image obtained from histologies of brain sections, which suggests an MLL modeling since the regions are spatially smooth. The presented algorithm maximizes the joint likelihood of the observations, y, and x given the unknown parameters. The parameters of the noise and the random field are estimated separately through a maximum likelihood technique given the current estimate of x, and the underlying field is estimated through a maximum a posteriori method. In the case of images modeled by MLL MRFs, the result of the restoration is actually a segmentation since the collection of all pixels with the same level defines a region. The results show that the algorithm successfully segments the region of interest even when the signal-to-noise ratio is low.
Starting Page	170
Ending Page	175
File Size	680160
Page Count	6
File Format	PDF
ISBN	0818620625
DOI	10.1109/ICPR.1990.119349
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1990-06-16
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image restoration Image segmentation Markov random fields Logistics Additive noise Gaussian noise Brain modeling Maximum likelihood estimation Maximum a posteriori estimation Signal restoration
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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