Multi-focus image fusion with half weighted gradient and self-similarity  

作　　者：DU Chao-ben LIU Ying GAO She-sheng 杜超本;刘颖;高社生(School of Automation,Northwestern Polytechnical University,Xi'an 710129,China;Center for Image and Information Processing,Xi'An University of Posts and Teleeommunications,Xi'an 710061,China)

机构地区：[1]School of Automation,Northwestern Polytechnical University,Xi'an 710129,China [2]Center for Image and Information Processing,Xi'An University of Posts and Teleeommunications,Xi'an 710061,China

出　　处：《Optoelectronics Letters》2018年第4期311-315,共5页光电子快报(英文版)

基　　金：supported by the National Natural Science Foundation of China(No.61174193)

摘　　要：In order to get a satisfactory image fusion effect,getting a focus map is very necessary and usually difficult to finish.In this paper,we address this problem with a half weighted gradient approach,aiming to obtain a direct mapping between focus map and source images.Based on the advantages of multi-scale weighted gradient,while abandoning the shortcomings of weighted gradient,a new multi-focus image fusion method called half weighted gradient and self-similarity(HWGSS)is proposed.Experimental results validate that the proposed algorithm can obtain state-of-the-art fusion performance in terms of both qualitative and quantitative evaluations.

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术]