NDLI: Dynamic Denoising of Tracking Sequences

Content Provider	IEEE Xplore Digital Library
Author	Michailovich, O. Tannenbaum, A.
Copyright Year	1992
Abstract	In this paper, we describe an approach to the problem of simultaneously enhancing image sequences and tracking the objects of interest represented by the latter. The enhancement part of the algorithm is based on Bayesian wavelet denoising, which has been chosen due to its exceptional ability to incorporate diverse a priori information into the process of image recovery. In particular, we demonstrate that, in dynamic settings, useful statistical priors can come both from some reasonable assumptions on the properties of the image to be enhanced as well as from the images that have already been observed before the current scene. Using such priors forms the main contribution of the present paper which is the proposal of the dynamic denoising as a tool for simultaneously enhancing and tracking image sequences. Within the proposed framework, the previous observations of a dynamic scene are employed to enhance its present observation. The mechanism that allows the fusion of the information within successive image frames is Bayesian estimation, while transferring the useful information between the images is governed by a Kalman filter that is used for both prediction and estimation of the dynamics of tracked objects. Therefore, in this methodology, the processes of target tracking and image enhancement "collaborate" in an interlacing manner, rather than being applied separately. The dynamic denoising is demonstrated on several examples of SAR imagery. The results demonstrated in this paper indicate a number of advantages of the proposed dynamic denoising over "static" approaches, in which the tracking images are enhanced independently of each other.
Sponsorship	IEEE Signal Processing Society
Page Count	10
File Size	2452501
Starting Page	847
Ending Page	856
File Format	PDF
ISSN	10577149
Volume Number	17
Issue Number	6
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-06-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Noise reduction Target tracking Layout Image sequences Bayesian methods Image enhancement Proposals Kalman filters Filtering Active contours wavelet denoising Bayesian estimation Kalman filtering predictive tracking
Content Type	Text
Resource Type	Article
Subject	Computer Graphics and Computer-Aided Design Software

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