کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
11012394 1800229 2018 17 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A deep learning framework for remote sensing image registration
ترجمه فارسی عنوان
چارچوب یادگیری عمیق برای ثبت تصویر تصویر سنجش از راه دور
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر سیستم های اطلاعاتی
چکیده انگلیسی
We propose an effective deep neural network aiming at remote sensing image registration problem. Unlike conventional methods doing feature extraction and feature matching separately, we pair patches from sensed and reference images, and then learn the mapping directly between these patch-pairs and their matching labels for later registration. This end-to-end architecture allows us to optimize the whole processing (learning mapping function) through information feedback when training the network, which is lacking in conventional methods. In addition, to alleviate the small data issue of remote sensing images for training, our proposal introduces a self-learning by learning the mapping function using images and their transformed copies. Moreover, we apply a transfer learning to reduce the huge computation cost in the training stage. It does not only speed up our framework, but also get extra performance gains. The comprehensive experiments conducted on seven sets of remote sensing images, acquired by Radarsat, SPOT and Landsat, show that our proposal improves the registration accuracy up to 2.4-53.7%.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: ISPRS Journal of Photogrammetry and Remote Sensing - Volume 145, Part A, November 2018, Pages 148-164
نویسندگان
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