一种使用局部空间统计量的高分辨率影像显著结构提取方法

A Method of Spatial Salient Structure Extraction Using Local Spatial Statistics in High Resolution Images

使用三个局部空间统计量(局部Moran’s I、局部Geary’s C和Getis)来建模影像的空间依赖性,提出了一种简单有效的获取影像显著结构的方法。该方法通过对空间依赖强度特征图像进行3D阈值化来获取影像的同质区或边缘结构,实验结果表明了这三个局部空间统计量在建模影像空间依赖性和获取显著结构方面的性能差异。

Homogeneous regions or edges are important structural information for object recognition and extraction in high resolution remote sensing images. This paper considers the homogeneous re-gions and edges from the perspective of spatial dependence, which is a measure of the spatial associa- tion between the pixel values in the image. Spatial dependence is one of the spatial characteristics of high resolution images. Based on the measure to spatial dependence using local spatial statistics （local Moran＇s I, local Geary＇s C and Getis）, this paper proposes a simple, effective method of extracting spatial salient structures （homogeneous regions or edges） which adopts a new technique of 3D thresh-olding for spatial dependence intensity. Comparative experiments show the potential and performance differences of three statistics in modeling spatial dependence and extracting spatial salient structures.