A Bayesian approach to edge detection in noisy images

被引：7

作者：

De Santis, A ^{[1
]}

Sinisgalli, C

机构：

[1] Univ Rome La Sapienza, Dipartimento Informat & Sistemist, I-00186 Rome, Italy

[2] Univ Rome La Sapienza, Dipartimento Informat & Sistemist, I-00184 Rome, Italy

来源：

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-FUNDAMENTAL THEORY AND APPLICATIONS | 1999年 / 46卷 / 06期

关键词：

Bayesian procedures; identification; image edge analysis; image processing; nonlinear estimation; segmentation;

D O I：

10.1109/81.768825

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

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.

引用

页码：686 / 699

页数：14

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