Multi-sensor image fusion based on contrast and directional features optimization

作     者：Jin, Haiyan Zhang, Meng Xiao, Zhaolin Li, Yaning 

作者机构：Xian Univ Technol Sch Comp Sci & Engn Xian 710048 Shaanxi Peoples R China Shaanxi Key Lab Network Comp & Secur Technol Xian Shaanxi Peoples R China 

出 版 物：《INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS》 (分布式传感网络国际杂志)

年 卷 期：2018年第14卷第12期

核心收录：

学科分类：0810[工学-信息与通信工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：National Natural Science Foundation of China 

主　　题：Image fusion multi-sensors directional features optimization whale optimization algorithm 

摘      要：Multi-sensor image fusion is always an important and opening problem, which can enhance visual quality and benefit some social security applications. In this article, we use contrast pyramid to decompose visible and infrared images, respectively, and the directional filter banks are applied to obtain multiple directional sub-band image features. Then, we compute the decomposition coefficients of visible and infrared images using a low-pass filter on the decomposed data;and finally, we introduce the whale optimization algorithm to search optimal coefficients to reconstruct the final fusion image. The experiments are conducted on multiple datasets with subjective and objective comparisons, in which the qualitative and quantitative analyses indicate the validity of the proposed method.