关键词: 遥感图像分割, 模糊聚类, 模糊迭代自组织数据分析技术算法（ISODATA）

Abstract: In traditional FISODATA algorithm, the splitting and merging operations need to choose a threshold manly. Sometimes, unsuitable threshold can cause an incorrect number of classes. This paper presents an improved fuzzy ISODATA algorithm. In the proposed algorithm, a new operation is designed for splitting and merging based on fuzzy set theory and changes the threshold by the results of the segmentation after it splits or merges, which makes it “adaptive”. It solves the problems caused by choosing threshold manly. Experimental results from a series of synthetic and IKONOS image segmentation demonstrate the adaptability and accuracy of the proposed approach over competing with other methods.

Key words: remote sensing image segmentation, fuzzy clustering, fuzzy Iterative Self-Organizing Data Analysis Techniques Algorithm（ISODATA）