Progressive decomposition of infrared and visible image fusion network with joint transformer and Resnet.

ABSTRACT: The objective of image fusion is to synthesize information from multiple source images into a single, high-quality composite that is information-rich, thereby enhancing both human visual interpretation and machine perception capabilities. This process also establishes a robust foundation for downstream image-related tasks. Nevertheless, current deep learning-based networks frequently neglect the distinctive features inherent in source images, presenting challenges in effectively balancing the interplay between basic and detailed features. To tackle this limitation, we introduce a progressive decomposition network that integrates Lite Transformer (LT) and ResNet architecture for infrared and visible image fusion (IVIF). Our methodology unfolds in three principal stages: Initially, a foundat

SUBMITTER: Zhu F 

PROVIDER: S-EPMC12373181 | biostudies-literature | 2025

REPOSITORIES: biostudies-literature