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Proceedings Paper

Unsupervised multiresolution segmentation and interpretation of textured SAR image
Author(s): Guoqing Liu; ShunJi Huang; Amalia Torre; Franco S. Rubertone
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Paper Abstract

With the wavelet transform theory and the Markov random model, this paper presents an unsupervised multiresohition segmentation method to segment the textured SAR image. This method specially includes a step to estimate both the optimal number of texture classes and their model parameters without supervision. In order to interpret the results of the unsupervised segmentation as well as to understand the whole polarimetric SAR image, this paper also develops an interpretation approach which jointly utilizes the target decomposition theory and the identification technique of the scattering mechanism. Experimental results are presented for demonstration.

Paper Details

Date Published: 17 December 1996
PDF: 11 pages
Proc. SPIE 2955, Image and Signal Processing for Remote Sensing III, (17 December 1996); doi: 10.1117/12.262895
Show Author Affiliations
Guoqing Liu, Univ. of Electronic Science and Technology of China (China)
ShunJi Huang, Univ. of Electronic Science and Technology of China (China)
Amalia Torre, Alenia Spazio SpA (Italy)
Franco S. Rubertone, Alenia Spazio SpA (Italy)

Published in SPIE Proceedings Vol. 2955:
Image and Signal Processing for Remote Sensing III
Jacky Desachy, Editor(s)

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