Benchmarking GPU-based phase correlation for homography-based registration of aerial imagery
Schubert, F and Mikolajczyk, K (2013) Benchmarking GPU-based phase correlation for homography-based registration of aerial imagery Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 8048 L (PART 2). pp. 83-90.
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Abstract
Many multi-image fusion applications require fast registration methods in order to allow real-time processing. Although the most popular approaches, local-feature-based methods, have proven efficient enough for registering image pairs at real-time, some applications like multi-frame background subtraction, super-resolution or high-dynamic-range imaging benefit from even faster algorithms. A common trend to speed up registration is to implement the algorithms on graphic cards (GPUs). However not all algorithms are specially suited for massive parallelization via GPUs. In this paper we evaluate the speed of a well-known global registration method, i.e. phase correlation, for computing 8-DOF homographies. We propose a benchmark to compare a CPU- and GPU-based implementation using different systems and a dataset of aerial imagery. We demonstrate that phase correlation benefits from GPU-based implementations much more than local methods, significantly increasing the processing speed. © 2013 Springer-Verlag.
Item Type: | Article |
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Divisions : | Surrey research (other units) |
Authors : | Schubert, F and Mikolajczyk, K |
Date : | 2013 |
DOI : | 10.1007/978-3-642-40246-3_11 |
Depositing User : | Symplectic Elements |
Date Deposited : | 28 Mar 2017 13:12 |
Last Modified : | 24 Jan 2020 12:24 |
URI: | http://epubs.surrey.ac.uk/id/eprint/806145 |
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