Block Adaptive Scalar-Vector Quantization Used to Compress SAR Raw Data

Shang Chun Zeng; Yun Xia Xie; Yi Xian Chen; Zhao Da Zhu

doi:10.4028/www.scientific.net/AMR.726-731.4650

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 726-731Block Adaptive Scalar-Vector Quantization Used to...

Block Adaptive Scalar-Vector Quantization Used to Compress SAR Raw Data

Abstract:

A block adaptive 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 doesnt satisfy. The experiments demonstrate that the performance of BASVQ algorithm surpasses that of BAQ algorithm. The BASVQ algorithm has practical value in some degree.

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Periodical:

Advanced Materials Research (Volumes 726-731)

Pages:

4650-4653

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.726-731.4650

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Online since:

August 2013

Authors:

Shang Chun Zeng, Yun Xia Xie, Yi Xian Chen, Zhao Da Zhu

Keywords:

Block Adaptive Quantization, Data Compression, Synthetic Aperture Radar (SAR), Vector Quantization

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References

[1] Shaohua Ye, Nansheng Sha, Zhaoda Zhu: Journal of Data Acquisition & Processing vol. 16(2001), pp.181-184 (In Chinese).

Google Scholar

[2] Pengzhi Cao, Rongqing Xu, Yongtan Liu: Journal of Harbin Institute of Technology vol. 29(1997), pp.91-94.

Google Scholar

[3] A. Moreira, F. Blaeser: In Proc., IGARSS'93, Tokyo vol. 4(1993), pp.1583-1585.

Google Scholar

[4] Zhenhong Guan, Daiyin Zhu, Zhaoda Zhu: Acta Aeronoutica et Astronautica Sinica vol. 27(2006), pp.82-86 (In Chinese).

Google Scholar

[5] W. Michael, Marcellin, T.R. Fischer: IEEE Transactions on Communications vol. 38(1990), pp.82-93.

Google Scholar

[6] R. Kwok, W.T.K. Johnson: IEEE Transactions on Geoscience and Remote Sensing vol. 27(1989), pp.375-383.

Google Scholar

[7] E.R. Caro: SIR-C: the Second Spaceborne Imaging Radar Symposium, Japan, vol., 6(1996)pp.109-114.

Google Scholar

[8] J. Max: IEEE Transactions on Information Theory vol. 28(1980), pp.84-95.

Google Scholar

[9] U. Benz: IEEE World Congress on Computational Intelligence vol. 2(1994), p.1006~1011.

Google Scholar

[10] Shenhe Sun, Zheming Lu. Vector quantization technology and application. Beijing: Science Publishing Company, (2002).

Google Scholar

[11] Xiaojun Wang, Hong Sun, Bao Guan: Systems Engineering and Electronics vol. 26(2004), pp.165-170 (In Chinese).

Google Scholar