Work place: Laboratory of Electronics and Microelectronics (EμE), Faculty of Sciences of Monastir University of Monastir, 5000, TUNISIA
Research Interests: Image Processing, Image Manipulation, Image Compression, Computer systems and computational processes
Mouna AFIF Received her master degree in micro and nano electronics from Monastir University in 2016. Currently she is a PHD student at the faculty of sciences of Monastir. She is working on image and video processing implementation on GPUs
DOI: https://doi.org/10.5815/ijigsp.2018.08.01, Pub. Date: 8 Aug. 2018
Convolution algorithms present a key component and a significant step in image processing field. Despite their high arithmetic complexity, these algorithms are widely used because of their great importance for extracting image properties and features. Convolution algorithms require significant computing time, for that we propose a GPU acceleration of these algorithms by using the programming language CUDA presented by NVIDIA. Since these algorithms consume a lot of computing power, we understand the impact of the implementation of this type of algorithm on the acceleration of processing. GPU implementation present a suitable path to achieve better results than other implementation , for that optimizing time consuming time consuming of applications became an increasingly important task in many research areas. The goal of this work is to try to boost convolution algorithms execution time by adopting GPU implementations to accelerate treatments and to achieve real time constraints.[...] Read more.
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