Academic Journal
أعرض في EDS

FPNFuse: A lightweight feature pyramid network for infrared and visible image fusion

التفاصيل البيبلوغرافية
العنوان: FPNFuse: A lightweight feature pyramid network for infrared and visible image fusion
المؤلفون: Zi‐Han Zhang, Xiao‐Jun Wu, Tianyang Xu
المصدر: IET Image Processing, Vol 16, Iss 9, Pp 2308-2320 (2022)
بيانات النشر: Wiley, 2022.
سنة النشر: 2022
المجموعة: LCC:Computer software
مصطلحات موضوعية: Photography, TR1-1050, Computer software, QA76.75-76.765
الوصف: Abstract A novel deep learning structure of infrared and visible image fusion is proposed. In particular, feature pyramid networks are developed for enhanced feature extraction across multiple convolutional layers. Besides, a fusion strategy is improved based on the channel attention mechanism to highlight the relevant attributes in the fusion stage. The fusion method consists of four parts: encoder, feature pyramid networks, fusion strategy and decoder, respectively. First, the multi‐scale deep features are extracted from the source images by encoder with embedded feature pyramid networks, realizing cross‐layer interaction. Second, these features are fused by the improved fusion strategy with channel attention for each scale. Finally, the fused features are reconstructed by the designed decoder to produce the informative fused image. The experimental results show that the proposed fusion method achieves state‐of‐the‐art results in both qualitative and quantitative evaluation with a lightweight architecture.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 1751-9667
1751-9659
Relation: https://doaj.org/toc/1751-9659; https://doaj.org/toc/1751-9667
DOI: 10.1049/ipr2.12473
URL الوصول: https://doaj.org/article/45d6c2727b374e878589664a7ca86d29
رقم الانضمام: edsdoj.45d6c2727b374e878589664a7ca86d29
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:17519667
17519659
DOI:10.1049/ipr2.12473