Abstract
Unlike conventional perspectives cameras, omnidirectional cameras allow to capture images with a large field of view. However, the resulting images contain important distortions that need to be taken into account in any image processing task. In this paper, we introduce a novel approach for omnidirectional images motion deblurring. We propose to adapt the Wiener deconvolution technique in order to takes into account the omnidirectional images geometry. We present a reformulation of the motion deblurring problem on the sphere which is considered as the most appropriate space for omnidirectional image processing. For this purpose, we develop a spherical Wiener filter using the necessary mathematical tools for spherical images processing and we model the motion blur using the velocity fields estimated via our omnidirectional optical flow estimation method. Experimental results show that our approach performs well on real and synthetic omnidirectional images.
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Alibouch, B., Rziza, M. (2021). Catadioptric Omnidirectional Images Motion Deblurring. In: Elbiaze, H., Sabir, E., Falcone, F., Sadik, M., Lasaulce, S., Ben Othman, J. (eds) Ubiquitous Networking. UNet 2021. Lecture Notes in Computer Science(), vol 12845. Springer, Cham. https://doi.org/10.1007/978-3-030-86356-2_25
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DOI: https://doi.org/10.1007/978-3-030-86356-2_25
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