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- Title
Acceleration of 3D feature-enhancing noise filtering in hybrid CPU/GPU systems.
- Authors
González-Ruiz, V.; Moreno, J. J.; Fernández, J. J.
- Abstract
FlowDenoising is a new approach to noise reduction in biological volumes obtained with three-dimensional electron microscopy (3DEM). Its abilities to enhance the structural features stem from the fact that an anisotropic Gaussian filtering is steered according to the local structures. To this end, the Optical Flow (OF) among consecutive slices is estimated, which is the most computationally expensive step in this approach. In this article, a hybrid CPU/GPU implementation of FlowDenoising is introduced and evaluated. It exploits parallel computing by distributing the workload among multiple cores and takes advantage of the massive processing in GPUs to accelerate the OF estimation. The hybrid implementation provides remarkable speed-up factors and an important reduction of the processing time, which is particularly relevant for the denoising of huge volumes typically found in 3DEM.
- Subjects
OPTICAL flow; NOISE control; ELECTRON microscopy; NOISE; PARALLEL programming; GRAPHICS processing units
- Publication
Journal of Supercomputing, 2024, Vol 80, Issue 9, p12727
- ISSN
0920-8542
- Publication type
Article
- DOI
10.1007/s11227-024-05928-x