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Proceedings Paper

Unsupervised classification of polarimetric SAR images using complex Wishart distribution based on H/α decomposition and algorithm evaluation
Author(s): Jie Yang; Ran Yang
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Paper Abstract

The authors introduce unsupervised wishart classification technique for fully polarimetric SAR data using H/α decomposition of POLSAR images. This paper we applied this technique to AIRSAR data of Flevoland, Netherlands. The most valuable in this paper is our evaluation. From the following tree aspects we evaluate the algorithm mentioned in this paper and the results it produced. (i) By calculating the Jeffries-Matusit Distance (J-M Distance) Jmn between two classes, which represents the separation between classes, the property of this classifier is measured. J-M Distance is a measurement of average difference between Probability Distribution Function (PDF) of two classes. Usually J-M Distance is between 0 and 2, and the bigger J-M Distance represents that two classes has a good separation. This paper we have most J-M Distances 1.8-2.0, thus indicates good separation; (ii) According to the average entropy and alpha of each final class, the classification results are analyzed; (iii) by comparing the classification results with the ground truth, the classification algorithm is evaluated. The results have a good simulation of ground truth. Experiment in this paper, according to the measurement criterion, analysis and evaluation, demonstrates that the region of Flevoland is well classification and the method has the advantage of edge holding that in the case of non-smooth borders this advantage is helpful. Also this paper gives a better repeat time.

Paper Details

Date Published: 14 November 2007
PDF: 8 pages
Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 679010 (14 November 2007); doi: 10.1117/12.748171
Show Author Affiliations
Jie Yang, Wuhan Univ. (China)
Ran Yang, Wuhan Univ. (China)


Published in SPIE Proceedings Vol. 6790:
MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications

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