In this paper a new morphological method is proposed for performing edge detection and image filtering at the same time. These operations are useful for high level image processing systems performing tasks such as pattern recognition or region segmentation. in literature two main classes of methodologies are proposed: Bayesian methods, that allow one to obtain good results with. the drawback of an expensive computational load, and Morphological Methods, that involve a better computational load and less accurate results. The proposed method is based on both mathematical morphological techniques and Markov Random Field based techniques. In this paper, experimental results are shown and it is possible to conclude that the method is suitable for processing images corrupted by structured impulsive noise (speckle noise) such as Synthetic Aperture Radar images.

New morphological approach to edge detection and image restoration

Regazzoni, Carlo S.;
1997-01-01

Abstract

In this paper a new morphological method is proposed for performing edge detection and image filtering at the same time. These operations are useful for high level image processing systems performing tasks such as pattern recognition or region segmentation. in literature two main classes of methodologies are proposed: Bayesian methods, that allow one to obtain good results with. the drawback of an expensive computational load, and Morphological Methods, that involve a better computational load and less accurate results. The proposed method is based on both mathematical morphological techniques and Markov Random Field based techniques. In this paper, experimental results are shown and it is possible to conclude that the method is suitable for processing images corrupted by structured impulsive noise (speckle noise) such as Synthetic Aperture Radar images.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11567/1105021
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