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Proceedings Paper

SAR raw data compression based on geometric characteristic of Gaussian curve
Author(s): Juan-ni Liu; Quan Zhou
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Paper Abstract

Because of simple and good performance, the block adaptive quantization (BAQ) algorithm becomes a popular method for spaceborne synthetic aperture radar (SAR) raw data compression. As the distribution of SAR data can be accurately modeled as Gaussian, the algorithm adaptively quantizes the SAR data using Llyod-Max quantizer, which is optimal for standard Gaussian signal. However, due to the complexity of the imaging target features, the probability distribution function of some SAR data deviates from the Gaussian distribution, so the BAQ compression performance declined. In view of this situation, this paper proposes a method to judge whether the data satisfies Gaussian distribution by using the geometrical relationship between standard Gaussian curve and a triangle whose area is equal to that of the Gaussian curve, then getting the coordinates of the intersection of two curves, and comparing the integral value within each node to form three judgment conditions. Finally, the data satisfying these conditions is compressed by BAQ, otherwise compressed by DPCM. Experimental results indicate that the proposed scheme improves the performance compared with BAQ method.

Paper Details

Date Published: 6 July 2015
PDF: 7 pages
Proc. SPIE 9631, Seventh International Conference on Digital Image Processing (ICDIP 2015), 96312H (6 July 2015); doi: 10.1117/12.2196919
Show Author Affiliations
Juan-ni Liu, Xi’an Institute of Space Radio Technology (China)
Quan Zhou, Xi’an Institute of Space Radio Technology (China)


Published in SPIE Proceedings Vol. 9631:
Seventh International Conference on Digital Image Processing (ICDIP 2015)
Charles M. Falco; Xudong Jiang, Editor(s)

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