Unsupervised multiresolution segmentation and interpretation of textured SAR image

Guoqing Liu; ShunJi Huang; Amalia Torre; Franco S. Rubertone

doi:10.1117/12.262895

17 December 1996 Unsupervised multiresolution segmentation and interpretation of textured SAR image

Guoqing Liu, ShunJi Huang, Amalia Torre, Franco S. Rubertone

Proceedings Volume 2955, Image and Signal Processing for Remote Sensing III; (1996) https://doi.org/10.1117/12.262895
Event: Satellite Remote Sensing III, 1996, Taormina, Italy

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.

Citation Download Citation

Guoqing Liu, ShunJi Huang, Amalia Torre, and Franco S. Rubertone "Unsupervised multiresolution segmentation and interpretation of textured SAR image", Proc. SPIE 2955, Image and Signal Processing for Remote Sensing III, (17 December 1996); https://doi.org/10.1117/12.262895

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