Multi‐domain pseudo‐reference quality evaluation for infrared and visible image fusion

Abstract Infrared and visible image fusion involves merging the advantages of infrared and visible images to generate a composite image that encompasses thermal radiation as well as intricate texture details. Infrared and visible image fusion has garnered increasing attention, with numerous fusion methods proposed. However, how to fairly perceive the performance of fused image remains a contentious topic. This paper is dedicated to solving this problem from two perspectives (e.g., subjective and objective aspects). Firstly, an infrared and visible fusion image quality assessment dataset was constructed, including 60 pairs of infrared and visible images captured in various scenes, along with 540 fusion images with different types and degrees of distortions. Additionally, a subjective evaluation dataset of 16,200 subjective scores by 30 participants was further provided for the fused image. Secondly, to overcome the challenging assessment for infrared and visible fusion images without a real reference image, an interesting multi‐domain pseudo‐reference image quality assessment model (MPIQAM) is proposed, by comprehensively considering the thermal radiation information distortion, texture information distortion, and overall naturalness of the fused image. The proposed MPIQAM was compared with 18 mainstream objective metrics, and the experimental findings showcased a commendable level of competitiveness.