Simultaneous parameter estimation and image segmentation for image sequence coding

Kristine E. Matthews; Nader M. Namazi

doi:10.1117/12.233179

27 February 1996 Simultaneous parameter estimation and image segmentation for image sequence coding

Kristine E. Matthews, Nader M. Namazi

Proceedings Volume 2727, Visual Communications and Image Processing '96; (1996) https://doi.org/10.1117/12.233179
Event: Visual Communications and Image Processing '96, 1996, Orlando, FL, United States

Abstract

We previously proposed and demonstrated the feasibility of a method for segmenting an image in a sequence of images into regions of stationary, moving, and uncovered background pixels and simultaneously estimating parameters of each region. The basis of our method is the expectation-maximization (EM) algorithm for maximum-likelihood estimation. We view the intensity difference between image frames as the incomplete data and the intensity difference with the region identifier as the complete data. Our previous work focused primarily on the viability of the method and considered only moving and stationary pixels. In particular, we estimated the DCT coefficients of the motion field for the moving pixels allowing motion- compensated reconstruction of image frames. In this paper we extend our previous formulation to include uncovered background pixels, and we present results showing image segmentation and parameter convergence.

Citation Download Citation

Kristine E. Matthews and Nader M. Namazi "Simultaneous parameter estimation and image segmentation for image sequence coding", Proc. SPIE 2727, Visual Communications and Image Processing '96, (27 February 1996); https://doi.org/10.1117/12.233179

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