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A Bayesian approach to edge detection in noisy images

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2 Author(s)
De Santis, A. ; Dipt. di Inf. e Sistemistica, Rome Univ., Italy ; Sinisgalli, C.

An adaptive method for edge detection in monochromatic unblurred noisy images is proposed. It is based on a linear stochastic signal model derived from a physical image description. The presence of an edge is modeled as a sharp local variation of the gray-level mean value. In any pixel, the statistical model parameters are estimated by means of a Bayesian procedure. Then an hypothesis test, based on the likelihood ratio statistics, is adopted to mark a pixel as an edge point. This technique exploits the estimated local signal characteristics and does not require any overall thresholding procedure

Published in:

Circuits and Systems I: Fundamental Theory and Applications, IEEE Transactions on  (Volume:46 ,  Issue: 6 )

Date of Publication:

Jun 1999

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