Neural network-based feature point descriptors for registration of optical and SAR images

Dmitry Abulkhanov; Ivan Konovalenko; Dmitry Nikolaev; Alexey Savchik; Evgeny Shvets; Dmitry Sidorchuk

doi:10.1117/12.2310085

13 April 2018 Neural network-based feature point descriptors for registration of optical and SAR images

Dmitry Abulkhanov, Ivan Konovalenko, Dmitry Nikolaev, Alexey Savchik, Evgeny Shvets, Dmitry Sidorchuk

Proceedings Volume 10696, Tenth International Conference on Machine Vision (ICMV 2017); 106960L (2018) https://doi.org/10.1117/12.2310085
Event: Tenth International Conference on Machine Vision, 2017, Vienna, Austria

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.

Citation Download Citation

Dmitry Abulkhanov, Ivan Konovalenko, Dmitry Nikolaev, Alexey Savchik, Evgeny Shvets, and Dmitry Sidorchuk "Neural network-based feature point descriptors for registration of optical and SAR images", Proc. SPIE 10696, Tenth International Conference on Machine Vision (ICMV 2017), 106960L (13 April 2018); https://doi.org/10.1117/12.2310085

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