Inputs and outputs at different levels.

<div><p>Abstract</p><p>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 a...

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Bibliographic Details
Main Author:	Fang Zhu (185566) (author)
Other Authors:	Wei Liu (20030) (author)
Published:	2025
Subjects:	Medicine Neuroscience Mental Health Space Science Biological Sciences not elsewhere classified Chemical Sciences not elsewhere classified Information Systems not elsewhere classified three principal stages strategically embedded within quantitative analyses conducted machine perception capabilities human visual interpretation final stage involves current deep learning conventional resnet preprocessing specialized fusion sub semantic injection module detailed feature components advanced visual tasks integrates lite transformer div >< p distinctive features inherent resnet </ p process also establishes cascade lt operations branch feature extraction progressive decomposition network multiple source images visible image fusion resnet network architecture source images image fusion progressive decomposition resnet architecture detailed features proposed network visible datasets related tasks lt module transformer decoders progressive inter joint transformer fused image downstream image scale features xlink "> thereby enhancing superior potential second phase robust foundation reconfigured blocks quality composite presenting challenges multiple infrared methodology unfolds layer extractions ivif ).
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Inputs and outputs at different levels.

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