Image and Signal Processing Methods

Simulation of spatially correlated PolSAR images using inverse transform method

[+] Author Affiliations
Xianxiang Qin, Huanxin Zou, Shilin Zhou, Kefeng Ji

National University of Defense Technology, College of Electronic Science and Engineering, Changsha 410073, China

J. Appl. Remote Sens. 9(1), 095082 (Apr 20, 2015). doi:10.1117/1.JRS.9.095082
History: Received August 21, 2014; Accepted March 19, 2015
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Abstract.  This paper proposes an algorithm of simulating spatially correlated polarimetric synthetic aperture radar (PolSAR) images based on the inverse transform method (ITM). Three flexible non-Gaussian models are employed as the underlying distributions of PolSAR images, including the KummerU, W and M models. Additionally, the spatial correlation of the texture component is considered, which is described by a parametric model called the anisotropic Gaussian function. In the algorithm, PolSAR images are simulated by multiplying two independent components, the speckle and texture, that are generated separately. There are two main contributions referring to two important aspects of the ITM. First, the inverse cumulative distribution functions of all the considered texture distributions are mathematically derived, including the Fisher, Beta, and inverse Beta models. Second, considering the high computational complexities the implicitly expressed correlation transfer functions of these texture distributions have, we develop an alternative fast scheme for their computation by using piecewise linear functions. The effectiveness of the proposed simulation algorithm is demonstrated with respect to both the probability density function and spatial correlation.

© 2015 Society of Photo-Optical Instrumentation Engineers

Topics

Simulations ; Speckle

Citation

Xianxiang Qin ; Huanxin Zou ; Shilin Zhou and Kefeng Ji
"Simulation of spatially correlated PolSAR images using inverse transform method", J. Appl. Remote Sens. 9(1), 095082 (Apr 20, 2015). ; http://dx.doi.org/10.1117/1.JRS.9.095082


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