Block adaptive scalar-vector quantization for SAR raw data compression

Shangchun Zeng; Yunxia Xie; Yixian Chen; Huazhang Wang

doi:10.1117/12.2030940

19 July 2013 Block adaptive scalar-vector quantization for SAR raw data compression

Shangchun Zeng, Yunxia Xie, Yixian Chen, Huazhang Wang

Author Affiliations +

Proceedings Volume 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013); 88781Q (2013) https://doi.org/10.1117/12.2030940
Event: Fifth International Conference on Digital Image Processing, 2013, Beijing, China

Abstract

The block adaptive quantization (BAQ) algorithm is comparatively mature for SAR raw data compression at present. This algorithm is on the premise that SAR raw data should satisfy Gauss distribution. But the imaged region is quite rugged, some blocks of data doesn’t satisfy Gaussian distribution. Therefore, a block adative scalar-vector quantization (BASVQ) algorithm is put forward in this paper, namely, scalar quantization is applied when data blocks satisfy Gaussian distribution while vector quantization is applied when doesn’t satisfy. The experiments demonstrate that the performance of BASVQ algorithm outperforms that of BAQ algorithm. The BASVQ algorithm has practical value in some degree.

Citation Download Citation

Shangchun Zeng, Yunxia Xie, Yixian Chen, and Huazhang Wang "Block adaptive scalar-vector quantization for SAR raw data compression", Proc. SPIE 8878, Fifth International Conference on Digital Image Processing (ICDIP 2013), 88781Q (19 July 2013); https://doi.org/10.1117/12.2030940

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