Advancing RGB-IR Image Fusion: Exploiting Hyperbolic Geometry

Infrared and visible image fusion is essential for remote sensing applications, especially for obtaining high-quality imagery of terrestrial environments. Hierarchical feature information is crucial for image fusion as it captures the intricate relationships between different modalities, which are v...

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Vydáno v:	IEEE journal of selected topics in applied earth observations and remote sensing Ročník 18; s. 6007 - 6016
Hlavní autoři:	Peng, Chenyu, Shen, Tao, Wang, Qingwang
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Piscataway IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Témata:	Computational modeling Computer vision Convolution Data models Deep learning Euclidean geometry Euclidean space Feature extraction Geometry Hyperbolic convolution Hyperbolic coordinates hyperbolic space Image fusion Image quality Infrared imagery Infrared imaging Multisensor fusion Neural networks Object detection Remote sensing Similarity Terrestrial environments Transformers
ISSN:	1939-1404, 2151-1535
On-line přístup:	Získat plný text
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