高分辨率SAR图像数据SIRV建模

SIRV Modeling for High Resolution SAR Image Data

针对目前对高分辨率陆地合成孔径雷达(SAR)图像数据特性缺乏充分研究的现状,文中通过验证实测数据与球不变随机向量(SIRV)模型的相容性,对荒漠的高分辨率图像数据进行建模。首先,对K-S检验进行改进,增强其在不独立数据样本中的健壮性;然后,采用K-S检验改进算法,验证实测数据的循环对称性,并在广义球坐标系下验证实测数据与SIRV模型的相容性;最后,根据SIRV模型中纹理分量的慢变特点,提出"一致区域"的概念,对图像进行局部化处理,从而简化了"一致区域"内的高阶统计特性分析。实验表明,文中提出的K-S检验改进算法对不独立杂波样本具有良好的健壮性,荒漠的高分辨率SAR图像数据与SIRV模型是相容的。通过对数据的分析,文中验证了"一致区域"概念的合理性,并确定了荒漠数据"一致区域"的空间尺度。

Considering the fact of the absence of statistical analysis about land image data of high-resolution SAR,the data of desert is modeled by studying the data＇s compatibility with SIRV model.Firstly,one enhanced version of K-S test based on data per-treatment is proposed here to improve its robustness in non-independent samples.Then,the data＇s circular symmetry and compatibility with SIRV model in generalized spherical coordinates is proved,using enhanced version of K-S test.Finally,to resolve the problem that the higher order statistical characteristic is mathematically tractable in SIRV model,the definition of ＂Coherence Region＂ is proposed,which means the image is processed locally,according to the viewpoint that the texture component is slowly-varying in SIRV model.The experiments show that the enhanced method of K-S test has perfect robustness for non-independent samples.The data for the desert are compatible with SIRV model.By data analysis,the rationality of the concept of ＂Coherence Region＂ is proved and the space scale of ＂Coherence Region＂ for desert data is found here.