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Dynamic Image Restoration and Fusion Based on Dynamic Degradation
In addition, a dynamic degradation kernel is proposed to improve the robustness of image restoration and fusion.
AE-Netv2: Optimization of Image Fusion Efficiency and Network Architecture
Finally, we explore the commonness and characteristics of different image fusion tasks, which provides a research basis for further research on the continuous learning characteristics of human brain in the field of image fusion.
AE-Net: Autonomous Evolution Image Fusion Method Inspired by Human Cognitive Mechanism
Firstly, the relationship between human brain cognitive mechanism and image fusion task is analyzed and a physical model is established to simulate human brain cognitive mechanism.
Non-linear and Selective Fusion of Cross-Modal Images
The human visual perception system has strong robustness in image fusion.
Cross-Modal Image Fusion Theory Guided by Subjective Visual Attention
In order to improve the robustness and contextual awareness of image fusion tasks, we proposed a multi-task auxiliary learning image fusion theory guided by subjective attention.
A Cross-Modal Image Fusion Method Guided by Human Visual Characteristics
The characteristics of feature selection, nonlinear combination and multi-task auxiliary learning mechanism of the human visual perception system play an important role in real-world scenarios, but the research of image fusion theory based on the characteristics of human visual perception is less.
