On the Color Visualization of Three-component Model-based Decomposition for Polarimetric SAR Data

Xun Wang, Dong Li, Yunhua Zhang, Jiefang Yang, Liting Liang
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Abstract

Applicable visualization strategies are required to achieve quick inspection and interpretation of polarimetric synthetic aperture radar (PolSAR) images. However, the visual effect of PolSAR images may be susceptible to the possibly existent large dynamic range of PolSAR data. In this paper, a simplified method for adjusting the large dynamic range of PolSAR data is developed, which is similar to the “MinMaxContrastMedian” technique adopted by Pottier et al. in their visualization strategy within the PolSARpro software. Based on this simplified method and the red-green-blue color model, a novel color visualization strategy for three-component model-based polarimetric decomposition is further proposed. The feasibility and validity of the proposed strategy is verified by the measured PolSAR data of Oberpfaffenhofen obtained by DLR L-band E-SAR.
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基于三分量模型分解的极化SAR数据颜色可视化研究
为了实现极化合成孔径雷达(PolSAR)图像的快速检测和判读,需要适用的可视化策略。然而,由于PolSAR数据可能存在较大的动态范围,PolSAR图像的视觉效果可能会受到影响。本文开发了一种调整PolSAR数据大动态范围的简化方法,该方法类似于Pottier等人在PolSARpro软件的可视化策略中采用的“MinMaxContrastMedian”技术。在此基础上,结合红绿蓝颜色模型,提出了一种新的基于三分量模型的极化分解颜色可视化策略。通过DLR l波段E-SAR对奥伯法芬霍芬的实测PolSAR数据验证了该策略的可行性和有效性。
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