Statistical approaches to ill-posed image processing problems such as restoration, segmentation and edge-detection have been proposed previously that were based on Markov random fields (MRFs). MRFs provide a regularization framework where a-priori knowledge expressed in a probabilistic way can be used together with available data for obtaining solutions characterized by a "good" global behaviour. A-priori knowledge and evidential knowledge can be used to specify constraints on the solution within a probabilistic functional. Observation models are necessary to capture evidential knowledge, i.e., the relations between the solution and data acquired either by a physical or a logical device. The present paper is based on a multilevel MRF approach introduced in Regazzoni (1994) and Regazzoni and Venetsanopoulos aiming at three different tasks: 1) to detect straight lines, 2) to restore the original image, and 3) to detect edge points. In particular, a new line detection approach is introduced, consisting in a progressive relaxation of the threshold used to establish the line presence in an appropriate parameter space. The method is applied to SAR remote sensing.
An adaptive probabilistic model for straight edge-extraction within a multilevel MRF framework
Regazzoni, C. S.;Serpico, S. B.
1995-01-01
Abstract
Statistical approaches to ill-posed image processing problems such as restoration, segmentation and edge-detection have been proposed previously that were based on Markov random fields (MRFs). MRFs provide a regularization framework where a-priori knowledge expressed in a probabilistic way can be used together with available data for obtaining solutions characterized by a "good" global behaviour. A-priori knowledge and evidential knowledge can be used to specify constraints on the solution within a probabilistic functional. Observation models are necessary to capture evidential knowledge, i.e., the relations between the solution and data acquired either by a physical or a logical device. The present paper is based on a multilevel MRF approach introduced in Regazzoni (1994) and Regazzoni and Venetsanopoulos aiming at three different tasks: 1) to detect straight lines, 2) to restore the original image, and 3) to detect edge points. In particular, a new line detection approach is introduced, consisting in a progressive relaxation of the threshold used to establish the line presence in an appropriate parameter space. The method is applied to SAR remote sensing.
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