基于区域合并影像分割技术的多尺度地表景观分析

分割是面向对象影像分析的前提，景观空间异质性特征给遥感信息获取提出了多尺度的要求。影像分割的多尺度分析以尺度效应与对象异质性最小原则为前提，描述多尺度效应分析的必要性与可行性。基于区域合并的分割原理与方法，为多尺度影像分析提供理论与技术支持，在两个样区进行多尺度影像分割技术的应用实践，分析基于区域合并的多尺度分割数据的几何丰富度与语义丰富度。

Landscape Multi-Scale Image Analysis Based on the Region Growing Segmentation

Segmentation is the basis of object-oriented image analysis. For many years, due to the increasing require for object-oriented image analysis, procedures for image segmentation have been a main research focus in this area. The aim of segmentation is to extract the interesting region from remote sensing image, so the region-based approach is the best way for image segmentation. The region growing method generates many meaningful objects through merging the spectral-similar neighboring pixels. Meanwhile landscape spatial heterogeneity requires multi-scale analysis with remote sensing information extraction. Each pattern or process has its inherent feature in different scales. To ensure high precision surface information, the remote sensing application model building on one scale image need to be modified if it is used on the other scale. The combination of image segmentation and multi-scale analysis becomes a new trend in remote sensing application. Based on the scale affect and minimum-heterogeneity rule, this paper presents the necessity and possibility of multi-scale affects analysis as well as the principle and practice of the region growing image segmentation. There are two sites to test the multi-scale image segmentation process. The results show the image objects richness of geometry and semantic information. Therefore this approach offers an optical solution for the object-oriented and multi-scale image analysis.