块自适应标量-矢量量化算法压缩SAR原始数据  

Block Adaptive Scalar-vector Quantization for SAR Raw Data Compression

作　　者：曾尚春[1] 朱兆达[1] 

机构地区：[1]南京航空航天大学401教研室,南京210016

出　　处：《中国图象图形学报》2007年第8期1349-1353,共5页Journal of Image and Graphics

摘　　要：块自适应量化(BAQ)算法是目前比较成熟的一种合成孔径雷达(SAR)原始数据压缩算法,该算法以SAR原始数据块满足高斯分布为前提。由于SAR成像区域很复杂,有些数据块可能不满足高斯分布,因此提出了一种块自适应标量-矢量量化算法(BASVQ),当数据块满足高斯分布时,采用标量量化;当数据块不满足高斯分布时,采用矢量量化。实验结果表明,块自适应标量-矢量量化算法在性能上优于BAQ算法,具有一定的实用价值。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, for example some blocks of data do not satisfy Gaussian distribution. Therefore, 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 it does not satisfy. The experiments demonstrate that the performance of BASVQ algorithm outperforms that of BAQ algorithm. The BASVQ algorithm has practical value to some degree.

关 键 词：块自适应量化 合成孔径雷达 数据压缩 矢量量化 

分 类 号：TN957.52[电子电信—信号与信息处理]