图像融合质量评价方法研究综述

图像融合质量评价方法研究综述*

杨艳春+，李娇，王阳萍

兰州交通大学电子与信息工程学院，兰州730070

Review of Image Fusion Quality Evaluation Methods *

YANG Yanchun +,LI Jiao,WANG Yangping

School of Electronic and Information Engineering,Lanzhou Jiaotong University,Lanzhou 730070,China

+Corresponding author:E-mail:yangyanchun102@https://www.360docs.net/doc/f914849973.html,

YANG Yanchun,LI Jiao,WANG Yangping.Review of image fusion quality evaluation methods.Journal of Frontiers of Computer Science and Technology,2018,12(7)：1021-1035.

Abstract:In the field of image fusion,it is very important to evaluate the quality of image fusion scientifically and specifically.This paper analyzes and summarizes the existing methods for objectively evaluating the quality of multiple image fusion,and conducts a targeted classification analysis based on the different points of reflection.The existing objective evaluation indexes are divided into three categories:the first is based on the statistical characteristics of the fusion image,the second is based on the objective evaluation index between the fusion image and the ideal reference image,the third is based on objective evaluation index between source images and the fusion image.This paper sum-marizes the existing objective evaluation methods and analyzes the latest objective methods of image fusion quality assessment.Finally,this paper analyzes and prospects the existing defects of the objective evaluation methods for image fusion quality and the future research trends,to further provide theoretical support for image fusion quality evaluation.

Key words:image fusion;subjective evaluation method;objective evaluation method;structural similarity

摘要：在图像融合领域中，如何科学、有针对性地对图像融合质量进行有效评价具有十分重要的意义。分析*The National Natural Science Foundation of China under Grant Nos.61562057，61162016,61462059(国家自然科学基金);the Pro-gram for Changjiang Scholars and Innovative Research Team in University under Grant No.IRT_16R36(长江学者和创新团队发展计划);the Youth Science Foundation of Lanzhou Jiaotong University under Grant No.2014006(兰州交通大学青年科学基金).Received 2017-10,Accepted 2018-03.

CNKI 网络出版:2018-03-07,https://www.360docs.net/doc/f914849973.html,/kcms/detail/11.5602.TP.20180307.1106.002.html

ISSN 1673-9418CODEN JKYTA8

Journal of Frontiers of Computer Science and Technology

1673-9418/2018/12(07)-1021-15

doi:10.3778/j.issn.1673-9418.1710001E-mail:fcst@https://www.360docs.net/doc/f914849973.html, https://www.360docs.net/doc/f914849973.html, Tel:+86-10-89056056万方数据