Proceedings Paper
Use of the generalized maximum-likelihood algorithm for estimation of Markovian-modeled image motion| Format | Member Price | Non-Member Price |
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Paper Abstract
A new iterative technique for frame-to-frame image motion estimation is introduced and impleniented. The algorithm presented in this paper is based on the maximum likelihood criterion and is referred to as the GML algorithm. This scheme requires the covariance function matrix of the motion a priori. For this reason a possible motion model will be introduced and implemented. Simulation experiments are presented which investigate the performance of the algorithm in conjunction with real and synthetic images. Key Words : Motion Compensation Maximum Likelihood Covariance Function Markovian Field.
Paper Details
Date Published: 1 November 1990
PDF: 11 pages
Proc. SPIE 1349, Applications of Digital Image Processing XIII, (1 November 1990); doi: 10.1117/12.23534
Published in SPIE Proceedings Vol. 1349:
Applications of Digital Image Processing XIII
Andrew G. Tescher, Editor(s)
PDF: 11 pages
Proc. SPIE 1349, Applications of Digital Image Processing XIII, (1 November 1990); doi: 10.1117/12.23534
Show Author Affiliations
Nader M. Namazi, Michigan Technological Univ. (United States)
David W. Foxall, Michigan Technological Univ. (United States)
Published in SPIE Proceedings Vol. 1349:
Applications of Digital Image Processing XIII
Andrew G. Tescher, Editor(s)
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