NDLI: Edge/region-based segmentation and reconstruction of underwater acoustic images by Markov random fields

Content Provider	IEEE Xplore Digital Library
Author	Murino, V. Trucco, A.
Copyright Year	1998
Description	Author affiliation: Dept. of Math. & Comput. Sci., Udine Univ., Italy (Murino, V.)
Abstract	This paper describes a technique for the reconstruction and segmentation of three-dimensional acoustical images using a coupled Random Fields able to actively integrate confidence information associated with acquired data. Beamforming, a method widely applied in acoustic imaging, is used to build a three-dimensional image, associated point by point with another kind of information representing the reliability (i.e. "confidence") of such an image. Unfortunately, this kind of images is plagued by several problems due to the nature of the signal and to the related sensing system, thus heavily affecting data quality. Specifically, speckle noise and the broad directivity characteristic of the sensor lead to very degraded images. In the proposed algorithm, range and confidence images are modelled as Markov Random Fields whose associated probability distributions are specified by a single energy functional. A three-fold process has been applied able to reconstruct, segment, and restore the involved acoustic images exploiting both types of data. Our approach showed better performances with respect to other MRF-based methods as well as classical methods disregarding reliability information. Optimal (in the Maximum A-Posteriori probability sense) estimates of the 3D and confidence images are obtained by minimizing the energy functional by using simulated annealing.
Starting Page	408
Ending Page	413
File Size	108370
Page Count	6
File Format	PDF
ISBN	0818684976
ISSN	10636919
DOI	10.1109/CVPR.1998.698638
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1998-06-25
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Image reconstruction Array signal processing Acoustic imaging Speckle Image sensors Sensor phenomena and characterization Acoustic sensors Degradation Markov random fields
Content Type	Text
Resource Type	Article
Subject	Computer Vision and Pattern Recognition Software

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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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