The edge detection problem in blurred and noisy 2-D signals is dealt with. An adaptive signal processing algorithm is proposed which marks edge points according to an hypothesis test which compares the likelihoods of two models describing the local signal behaviour in the two cases of absence/presence of an edge. The two models are identi"ed by a regularized least squares estimation algorithm, obtaining a numerically e$cient procedure, quite robust with respect to additive noise and blurr perturbation. No global thresholding or data pre"ltering is required.
An efficient adaptive algorithm for edge detection based on the likelihood ratio test / DE SANTIS, Alberto; Iacoviello, Daniela. - In: INTERNATIONAL JOURNAL OF ADAPTIVE CONTROL AND SIGNAL PROCESSING. - ISSN 0890-6327. - STAMPA. - 16:4(2002), pp. 289-308. [10.1002/acs.701]
An efficient adaptive algorithm for edge detection based on the likelihood ratio test
DE SANTIS, Alberto;IACOVIELLO, Daniela
2002
Abstract
The edge detection problem in blurred and noisy 2-D signals is dealt with. An adaptive signal processing algorithm is proposed which marks edge points according to an hypothesis test which compares the likelihoods of two models describing the local signal behaviour in the two cases of absence/presence of an edge. The two models are identi"ed by a regularized least squares estimation algorithm, obtaining a numerically e$cient procedure, quite robust with respect to additive noise and blurr perturbation. No global thresholding or data pre"ltering is required.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
