Multiresolution image fusion scheme based on fuzzy region feature

This paper proposes a novel region based image fusion scheme based on multiresolution analysis. The low frequency band of the image multiresolution representation is segmented into important regions, sub-important regions and background regions. Each feature of the regions is used to determine the region’s degree of membership in the multiresolution representation, and then to achieve multiresolution representation of the fusion result. The final image fusion result can be obtained by using the inverse multiresolution transform. Experiments showed that the proposed image fusion method can have better performance than existing image fusion methods.

基于FRC框架的红外与可见光图像融合方法

像素级图像融合方案多采用全局统一的融合规则,融合过程易导致区域层级信息丢失.对此,提出一种基于模糊区域特征(FRC)框架的红外与可见光图像融合方法.首先,制定一种模糊区域规则,该规则依据区域特征的模糊性质,对源图像依次施行区域分割、模糊判定和解模糊,全局图像的融合转化为3种不同属性区域的融合;然后,分别对目标区域、过渡区域和背景区域采用期望值最大(EM)、加权平均融合、主成分分析(PCA)的融合策略进行融合;最后,融合后的区域图重构得到最终的融合图像.为验证FRC框架保护区域特征的有效性,还提出一种区域特征一致性的度量指标(RCABF),经主观视觉与客观指标检验,融合图像在保持红外目标显著性的同时,具有清晰的背景细节,优于现有的红外与可见光图像融合方法,宜应用于红外目标的监控与分析.