航空学报 > 2006, Vol. 27 Issue (1): 82-86

块自适应球形矢量量化算法压缩SAR原始数据

关振红, 朱兆达, 朱岱寅   

  1. 南京航空航天大学 信息学院, 江苏 南京 210016
  • 收稿日期:2004-11-22 修回日期:2005-01-27 出版日期:2006-02-25 发布日期:2006-02-25

Compression of SAR Raw Data by Block Adaptive Spherical Vector Quantization

GUAN Zhen-hong, ZHU Zhao-da, ZHU Dai-yin   

  1. College of Information Science and Technology, Nanjing University Aeronautics and Astronautics, Nanjing 210016, China
  • Received:2004-11-22 Revised:2005-01-27 Online:2006-02-25 Published:2006-02-25

摘要: 提出使用块自适应球形矢量量化算法压缩SAR原始数据,该算法充分利用SAR原始数据经过自适应块处理之后在较小的数据块范围内具有稳定高斯分布的特点,使用格型矢量技术中的球形码书量化器进行量化,可以提高算法的压缩性能。通过运用球形矢量量化算法对SAR原始数据进行压缩、解压缩获取相应的SAR图像与块自适应量化和块自适应矢量量化经过同样过程得到SAR图像进行比较分析,得出块自适应球形格矢量量化算法是算法复杂度和算法性能之间比较好的折中。

关键词: 合成孔径雷达(SAR), 球形矢量量化, 块自适应量化, 矢量量化

Abstract: In this paper,we propose to employ the block adaptive spherical vector quantization for compression of synthetic aperture radar (SAR) raw data.This algorithm exploits the known result that a blockwise normalized SAR raw signal is a Gaussian stationary process.With the comparison and analysis of quality parameters computed on the image, the proposed block adaptive spherical vector quantization shows an interesting performance/complexity trade-off, with respect to other algorithms such as the block adaptive quantization and the block adaptive vector quantization.

Key words: SAR, spherical vector quantization, block adaptive quantization, vector quantization

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