Please use this identifier to cite or link to this item: http://hdl.handle.net/10553/35392
Title: Block matching super-resolution parallel GPU implementation for computational imaging
Authors: Marenzi, E
Torti, E.
Leporati, F.
Quevedo, Eduardo 
Marrero Callicó, Gustavo 
UNESCO Clasification: 220990 Tratamiento digital. Imágenes
Keywords: Image enhancement
Motion estimation
Parallelization
Super-Resolution
Issue Date: 2017
Journal: IEEE Transactions on Consumer Electronics 
Abstract: This work presents the computational acceleration of a proprietary Super-Resolution (SR) algorithm (patented) for image and video enhancement. The considered algorithm is based on fusion SR techniques. The version proposed in this paper consists on the comparison of frames divided into Macro Blocks (MB) of fixed dimensions and on acquisition from a single camera. Due to its intensive computation, that limits its practical application in specific contexts where fast processing (even with real-time constraints) is necessary, the algorithm has been implemented in two platforms: OpenMP and GPU. Several tests have been conducted on seven popular image sequences and the results show a considerable improvement of the proposed solutions, in particular the Graphic Processing Units implementations. Consequently, it can be stated that GPUs represent an efficient solution to accelerate this type of algorithms to improve the perception of the image quality.
URI: http://hdl.handle.net/10553/35392
ISSN: 0098-3063
DOI: 10.1109/TCE.2017.015077
Source: IEEE Transactions on Consumer Electronics [ISSN 0098-3063], v. 63 (4), p. 368-376, article number 8246793
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