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Design and theoretical analysis of a vector field segmentation algorithm

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2 Author(s)
I. B. Kerfoot ; Beckman Inst., Illinois Univ., Urbana, IL, USA ; Y. Bresler

Several objective functions for vector field segmentation are presented. Y. G. Leclerc's (1989) MRF (Markov random field) model is extended by the addition of information-theoretic penalties for regions and distinct means. Standard methods of signal detection and estimation are used to develop a theoretical performance analysis which quantitatively predicts the performance at realistic noise levels. The theoretical performance analysis demonstrates the need for qualitative change from the scalar case; separate penalties for boundary structure and region existence are very beneficial for high d (dimensional). The theoretical analysis also indicates the merit of an objective function before an optimization algorithm has been developed. It also serves as a benchmark for optimization algorithm performance. Theoretical and experimental results agree fairly well.<>

Published in:

Acoustics, Speech, and Signal Processing, 1993. ICASSP-93., 1993 IEEE International Conference on  (Volume:5 )

Date of Conference:

27-30 April 1993