Scheduled System Maintenance:
On May 6th, system maintenance will take place from 8:00 AM - 12:00 PM ET (12:00 - 16:00 UTC). During this time, there may be intermittent impact on performance. We apologize for the inconvenience.
By Topic

Estimation of generalized mixture in the case of correlated sensors

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

The purchase and pricing options are temporarily unavailable. Please try again later.
3 Author(s)
Pieczynski, W. ; Dept. Signal et Image, Inst. Nat. des Telecommun., Evry, France ; Bouvrais, J. ; Michel, C.

This paper deals with unsupervised Bayesian classification of multidimensional data. We propose an extension of a previous method of generalized mixture estimation to the correlated sensors case. The method proposed is valid in the independent data case, as well as in the hidden Markov chain or field model case, with known applications in signal processing, particularly speech or image processing. The efficiency of the method proposed is shown via some simulations concerning hidden Markov fields, with application to unsupervised image segmentation

Published in:

Image Processing, IEEE Transactions on  (Volume:9 ,  Issue: 2 )