摘要： 传统图像融合质量评价方法的评价结果与人眼主观感知结果不一致，针对该问题，提出基于分水岭算法的图像融合质量评价方法。利用结构相似性理论获得源图像之间的结构相似信息图，运用分水岭算法对信息图进行分割。为减少过分割现象，在分水岭算法中应用标记符，将源图像的信息分为共有信息和互补信息，构建基于结构相似性的映射函数，分别处理共有信息和互补信息，完成融合图像质量评价。实验结果表明，与Piella和Zheng方法相比，该方法的抗干扰性能较好。

关键词: 分水岭算法, 图像融合, 质量评价, 结构相似度, 客观评价, 主观评价

Abstract: To the problem that objective image fusion quality assessment is not consistent with the subjective quality assessment, this paper puts forward an image fusion quality assessment method based on watershed algorithm. It utilizes the structure similarity theory to acquire the structure similarity information map, and applies watershed algorithm to segment the information map. In order to reduce the excessive segment phenomena, it makes the tag in the watershed and divides the image information into mutual information and independent information. It designs the mapping functions that process the mutual information and independent information separately, and accomplishes the fusion image quality assessment. Experimental results show that, compared with traditional methods, this method has advantage in anti-disturbance.

Key words: watershed algorithm, image fusion, quality assessment, structural similarity, objective assessment, subjective assessment

中图分类号: 

• TN911.73