Infrared and visible image fusion via global variable consensus

作者：

Highlights：

• We propose a novel image fusion framework to generate high-quality fusion results with different image features.

• The model is based on the theory of the consensus problem.

• In our model the fusion result is generated with different type of features extracted separately from source images.

• We unified regularize the model in order to handle the over-fitting problem, which leads to low-quality fusion results.

摘要

•We propose a novel image fusion framework to generate high-quality fusion results with different image features.•The model is based on the theory of the consensus problem.•In our model the fusion result is generated with different type of features extracted separately from source images.•We unified regularize the model in order to handle the over-fitting problem, which leads to low-quality fusion results.

论文关键词：Image fusion,Infrared,Consensus,Total variation,ADMM

论文评审过程：Received 24 June 2020, Revised 3 September 2020, Accepted 23 September 2020, Available online 30 September 2020, Version of Record 10 October 2020.

论文官网地址：https://doi.org/10.1016/j.imavis.2020.104037