数据融合的概念应用在遥感图像的自动特征提取中,可以利用数据的互补和冗余来改善特征提取的性能.由于经典理论交集和并集的外延法不能得到满意的结果(相应的算子过于严格或是过于宽松),对这两个具有对立特性的算子进行折衷,可以得到较为满意的结果.运用上下文依赖模糊算子实现这种折衷,对其加权因子的构造提出了新的设想和算法.参照计算机模拟的结果,分析和讨论了它的特点.

Data redundancy can improve the performance of automatic feature extraction in remote sensing image if the concept of data fusion is applied in it. Extensions of classical set union and intersection do not lead to satisfactory results (the corresponding operators are either too indulgent or too severe), but fusing two operators that have opposite properties can obtain an obvious result. In this paper, context dependent fuzzy operator is used to achieve this compromise, and a new formation of weights is proposed. Based on the simulative result, the performance of this method is discussed.