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Rectification for Stitched Images with Deformable Meshes and Residual Networks

التفاصيل البيبلوغرافية
العنوان: Rectification for Stitched Images with Deformable Meshes and Residual Networks
المؤلفون: Yingbo Fan, Shanjun Mao, Mei Li, Zheng Wu, Jitong Kang, Ben Li
المصدر: Applied Sciences, Vol 14, Iss 7, p 2821 (2024)
بيانات النشر: MDPI AG, 2024.
سنة النشر: 2024
المجموعة: LCC:Technology
LCC:Engineering (General). Civil engineering (General)
LCC:Biology (General)
LCC:Physics
LCC:Chemistry
مصطلحات موضوعية: image rectangular, deformable mesh, width residual network, global loss function, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
الوصف: Image stitching is an important method for digital image processing, which is often prone to the problem of the irregularity of stitched images after stitching. And the traditional image cropping or complementation methods usually lead to a large number of information loss. Therefore, this paper proposes an image rectification method based on deformable mesh and residual network. The method aims to minimize the information loss at the edges of the spliced image and the information loss inside the image. Specifically, the method can select the most suitable mesh shape for residual network regression according to different images. Its loss function includes global loss and local loss, aiming to minimize the loss of image information within the grid and global target. The method in this paper not only greatly reduces the information loss caused by irregular shapes after image stitching, but also adapts to different images with various rigid structures. Meanwhile, its validation on the DIR-D dataset shows that the method outperforms the state-of-the-art methods in image rectification.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2076-3417
Relation: https://www.mdpi.com/2076-3417/14/7/2821; https://doaj.org/toc/2076-3417
DOI: 10.3390/app14072821
URL الوصول: https://doaj.org/article/36432268addd4b62aa9f310a5bf9acd3
رقم الأكسشن: edsdoj.36432268addd4b62aa9f310a5bf9acd3
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20763417
DOI:10.3390/app14072821