顾及冲突分析的模糊积分非监督变化检测

以模糊积分(Fuzzy integral, FI)为基础, 提出一种顾及冲突分析(Conflict analysis, CA)的全自动遥感变化检测方法CA-based FI, CAFI). CAFI首先选取典型的对比算子, 生成信息互补的差异图(Difference image, DI)集; 其次利用模糊聚类、杰卡德相似系数和FI对差异图进行决策级融合, 得到初步融合变化检测图; 然后通过模糊集理论计算像元的信息冲突程度, 将初步融合检测结果自适应地划分为冲突严重区域和冲突较弱区域; 最后, 对冲突较弱的像元, 将其初步融合结果作为最终检测结果, 对易产生融合错误的冲突严重像元, 利用地统计分析对其重新分类. CAFI能够集成不同信息优势的同时, 很大程度地解决FI融合过程中的信息冲突问题. 三组真实遥感数据的实验结果验证了CAFI的有效性和鲁棒性.

Unsupervised Change Detection Based on Fuzzy Integral Considering Conflict Analysis

This paper presents an automatic change detection method incorporating conflict analysis (CA) based on fuzzy integral (CAFI) for multitemporal remote sensing images. First, a difference image (DI) set with complementary information is generated by selecting typical comparison operators. Second, the DIs are fused in decision level by fuzzy clustering, Jaccard similarity coefficient and fuzzy integral, and a preliminary change detection map is obtained. Third, the preliminary map is adaptively partitioned into two regions — strongly conflicting region and weakly conflicting region — by computing the information conflict degree of each pixel with fuzzy set theory. Finally, for the weakly conflicting pixels, their preliminary detecting results are taken as the final results; and the strongly conflicting pixels likely to be misclassified are reclassified based on geostatistical analysis. CAFI can integrate the advantages of different DI images and resolve the FI conflicting situations largely. Experimental results on three real remote sensing images verify the effectiveness and robustness of the proposed technique.