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논문 기본 정보

자료유형
학술저널
저자정보
Shunyuan Yang (Harbin Institute of Technology) Xiaoping Shi (Harbin Institute of Technology) Ju Huo (National Key Laboratory of Modeling and Simulation for Complex Systems) Kangjian Sun (National Key Laboratory of Modeling and Simulation for Complex Systems) Yu Wang (Shanghai Space Propulsion Technology Research Institute)
저널정보
한국광학회 Current Optics and Photonics Current Optics and Photonics Vol.9 No.2
발행연도
2025.4
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120 - 129 (10page)

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초록· 키워드

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In the field of optics, infrared and visible images are often required for use in different situations. In particular, in the field of optical sensors, infrared and visible sensors are mainly used to obtain different band images, which are applied to improve the comprehensive information content of images and to improve the quality and availability of images. In existing infrared and visible image fusion methods, the focus is often placed on retaining the background information from visible images and the salient targets from infrared images. To address this issue, we introduce a multi-scale dilated attention module into the encoder-decoder structure of the generator. By applying dilated convolution and selfattention mechanisms, this module improves the perceptual capability of the model, thereby improving performance without increasing network complexity. This design emphasizes gradient information and detailed features in visible images. Experimental results on the public TNO dataset demonstrate that our method achieves superior visual quality and preserves the most abundant image information. Moreover, experiments on spacecraft images validate the robustness and applicability of our approach. Simultaneously, our method also provides significant technical support for the optical field.

목차

Ⅰ. INTRODUCTION
Ⅱ. RELATED WORK
Ⅲ. PROPOSED METHOD
Ⅳ. EXPERIMENTS
Ⅴ. CONCLUSIONS
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