Unsupervised classification of polarimetric SAR images using complex Wishart distribution based on H/&#945; decomposition and algorithm evaluation

Jie Yang; Ran Yang

doi:10.1117/12.748171

14 November 2007 Unsupervised classification of polarimetric SAR images using complex Wishart distribution based on H/α decomposition and algorithm evaluation

Jie Yang, Ran Yang

Author Affiliations +

Proceedings Volume 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications; 679010 (2007) https://doi.org/10.1117/12.748171
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

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) J_mn 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.

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Jie Yang and Ran Yang "Unsupervised classification of polarimetric SAR images using complex Wishart distribution based on H/α decomposition and algorithm evaluation", Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 679010 (14 November 2007); https://doi.org/10.1117/12.748171

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KEYWORDS

Polarimetry

Image classification

Synthetic aperture radar

Coherence (optics)

Distance measurement

Data storage

Image processing algorithms and systems

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