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Neural network-based feature point descriptors for registration of optical and SAR images
Author(s): Dmitry Abulkhanov; Ivan Konovalenko; Dmitry Nikolaev; Alexey Savchik; Evgeny Shvets; Dmitry Sidorchuk
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Paper Abstract

Registration of images of different nature is an important technique used in image fusion, change detection, efficient information representation and other problems of computer vision. Solving this task using feature-based approaches is usually more complex than registration of several optical images because traditional feature descriptors (SIFT, SURF, etc.) perform poorly when images have different nature. In this paper we consider the problem of registration of SAR and optical images. We train neural network to build feature point descriptors and use RANSAC algorithm to align found matches. Experimental results are presented that confirm the method’s effectiveness.

Paper Details

Date Published: 13 April 2018
PDF: 8 pages
Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 106960L (13 April 2018); doi: 10.1117/12.2310085
Show Author Affiliations
Dmitry Abulkhanov, Institute for Information Transmission Problems (Russian Federation)
Ivan Konovalenko, Institute for Information Transmission Problems (Russian Federation)
Dmitry Nikolaev, Institute for Information Transmission Problems (Russian Federation)
Alexey Savchik, Institute for Information Transmission Problems (Russian Federation)
Evgeny Shvets, Institute for Information Transmission Problems (Russian Federation)
Dmitry Sidorchuk, Institute for Information Transmission Problems (Russian Federation)


Published in SPIE Proceedings Vol. 10696:
Tenth International Conference on Machine Vision (ICMV 2017)
Antanas Verikas; Petia Radeva; Dmitry Nikolaev; Jianhong Zhou, Editor(s)

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