中文摘要：

高分辨率遥感影像中丰富的空间结构信息和地理特征信息提取需要在多种不同的尺度下进行,而传统的基于像素光谱特征的影像分割和单尺度影像信息提取方法在这方面存在明显的缺陷.基于区域的面向对象影像分析方法,为高分辨率遥感影像信息提取提供了新的思路,其关键的核心问题在于实现对高分辨率遥感影像的多尺度分割.本文提出了一种基于相邻影像区域合并异质性最小的面向对象多尺度分割算法.影像分割试验结果表明：该方法可以根据任意特定尺度下的影像分析任务或任意感兴趣尺度的地物目标,调整影像分割的尺度参数,从而获得特定尺度下感兴趣的影像区域（对象）作为后续面向对象影像分析和应用的基础.

英文摘要：

In order to utilize the rich scale-dependent information contained in high resolution remote sensing images, the geo-science applications of remote sensing image and geographical information extraction must be carried out under multi-scale condition. Therefore, the conventional developed image segmentation methods for only one scale can＇t meet these requirements. In this paper, an object oriented multi-scale image segmentation method is introduced based on minimum heterogeneity criterion of neighbouring region growing. This procedure can easily adapt its scale parameter to different scale image analysis tasks and any chosen scale object-extraction of interest. In a word, it can provide enormous object characteristics for further object-oriented processing or analysis.