The Highly Compressed PolSAR Model

John Becker;Julie Ann Jackson
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Abstract

Additional scene information can be captured using fully polarimetric synthetic aperture radar (PolSAR) at the cost of significant increases in storage and data processing requirements. The typically sparse nature of PolSAR scenes makes compressed sensing (CS) techniques very attractive to help alleviate the increased processing and storage requirements. Here, the authors combine techniques for fast- and slow-time undersampling as well as the dropped-channel PolSAR CS technique to create a new highly compressed PolSAR model. Examples of both point target and real-world scenes are then used to demonstrate the model. Compression rates of up to 98.92% are observed for sufficiently sparse scenes.
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高压缩 PolSAR 模型
使用全偏振合成孔径雷达(PolSAR)可以捕捉到更多的场景信息,但代价是存储和数据处理要求大幅增加。PolSAR 场景通常比较稀疏,这使得压缩传感(CS)技术非常有吸引力,有助于减轻处理和存储要求的增加。在此,作者将快速和慢速时间欠采样技术与丢弃信道 PolSAR CS 技术相结合,创建了一种新的高度压缩 PolSAR 模型。然后使用点目标和真实世界场景的示例来演示该模型。在足够稀疏的场景中,压缩率高达 98.92%。
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