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Image rectangling network based on reparameterized transformer and assisted learning

التفاصيل البيبلوغرافية
العنوان: Image rectangling network based on reparameterized transformer and assisted learning
المؤلفون: Lichun Yang, Bin Tian, Tianyin Zhang, Jiu Yong, Jianwu Dang
المصدر: Scientific Reports, Vol 14, Iss 1, Pp 1-11 (2024)
بيانات النشر: Nature Portfolio, 2024.
سنة النشر: 2024
المجموعة: LCC:Medicine
LCC:Science
مصطلحات موضوعية: Image rectangling, Single wrap, Re-parameterization, Assisted learning, Medicine, Science
الوصف: Abstract Stitched images can offer a broader field of view, but their boundaries can be irregular and unpleasant. To address this issue, current methods for rectangling images start by distorting local grids multiple times to obtain rectangular images with regular boundaries. However, these methods can result in content distortion and missing boundary information. We have developed an image rectangling solution using the reparameterized transformer structure, focusing on single distortion. Additionally, we have designed an assisted learning network to aid in the process of the image rectangling network. To improve the network’s parallel efficiency, we have introduced a local thin-plate spline Transform strategy to achieve efficient local deformation. Ultimately, the proposed method achieves state-of-the-art performance in stitched image rectangling with a low number of parameters while maintaining high content fidelity. The code is available at https://github.com/MelodYanglc/TransRectangling .
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2045-2322
Relation: https://doaj.org/toc/2045-2322
DOI: 10.1038/s41598-024-56589-y
URL الوصول: https://doaj.org/article/79751038ca7445d6bbcf7b7bc32d7a8c
رقم الأكسشن: edsdoj.79751038ca7445d6bbcf7b7bc32d7a8c
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20452322
DOI:10.1038/s41598-024-56589-y