为了提高分类精度和边缘辨识性,该文引入图像空间一致性降元(pixels reduction with spatialcoherence property,PRSCP)及线性回归分析,提出了一种基于空间一致性降元的非监督分类。该方法从像元光谱相似性出发,利用像元最小关联窗口合...为了提高分类精度和边缘辨识性,该文引入图像空间一致性降元(pixels reduction with spatialcoherence property,PRSCP)及线性回归分析,提出了一种基于空间一致性降元的非监督分类。该方法从像元光谱相似性出发,利用像元最小关联窗口合并相邻相似像元为像块完成降元。使用线性关系建模像块内像元的光谱向量,并利用F检验判断像块数据的线性显著性。利用一元线性回归(one dimensional linear regression,ODLR)估计出像块的基准向量,根据基准向量合并相似(同类)像块完成分类。利用AVIRIS数据评估了该方法性能,实验结果表明:与K-MEANS和ISODATA方法相比,该方法精度高、边缘辨识度好及鲁棒性强。展开更多
The limit properties of spatial coherence of seismic ground motion are studied based on the differential relation between rotation and translation in elastic theory, the results show that the empirical mathematical mo...The limit properties of spatial coherence of seismic ground motion are studied based on the differential relation between rotation and translation in elastic theory, the results show that the empirical mathematical model of spatial coherence must satisfy some functional characteristics. It is also indicated that the key problem to estimate rotational power spectrum densities is to obtain precisely the two order derivative of spatial coherence.展开更多
文摘为了提高分类精度和边缘辨识性,该文引入图像空间一致性降元(pixels reduction with spatialcoherence property,PRSCP)及线性回归分析,提出了一种基于空间一致性降元的非监督分类。该方法从像元光谱相似性出发,利用像元最小关联窗口合并相邻相似像元为像块完成降元。使用线性关系建模像块内像元的光谱向量,并利用F检验判断像块数据的线性显著性。利用一元线性回归(one dimensional linear regression,ODLR)估计出像块的基准向量,根据基准向量合并相似(同类)像块完成分类。利用AVIRIS数据评估了该方法性能,实验结果表明:与K-MEANS和ISODATA方法相比,该方法精度高、边缘辨识度好及鲁棒性强。
文摘The limit properties of spatial coherence of seismic ground motion are studied based on the differential relation between rotation and translation in elastic theory, the results show that the empirical mathematical model of spatial coherence must satisfy some functional characteristics. It is also indicated that the key problem to estimate rotational power spectrum densities is to obtain precisely the two order derivative of spatial coherence.
