@inproceedings{ea91d8b5fc7143fbb6de4ec8bff973c9,
title = "Parallel image dehazing algorithm based on GPU using fuzzy system and hybird evolution algorithm",
abstract = "Haze is an atmospheric phenomenon that fogs the visibility of the scenes. Removing the haze has been an important issue in image processing technologies. Many image dehazing technologies with evolution algorithms have been proposed to remove the fog in the image. However, these algorithms usually are compute-intensive. In this paper, we propose a parallel hybrid evolution algorithm based on GPU to enhance the computational performance. In traditional evolution algorithms, the calculation of fitness function occupies the most of the computation time. In the proposed method, we implement this part on GPU by using CUDA framework to reduce the computational load. The experiment results show that the proposed method can remove the haze efficiently and successfully.",
keywords = "CUDA, Evolution, GPU, Image Dehazing, Parallel Computing",
author = "Hung, {Che Lun} and Yan, {Ren You} and Wang, {Hsiao Hsi}",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; null ; Conference date: 30-05-2016 Through 01-06-2016",
year = "2016",
month = jul,
day = "18",
doi = "10.1109/SNPD.2016.7515962",
language = "English",
series = "2016 IEEE/ACIS 17th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "581--583",
editor = "Yihai Chen",
booktitle = "2016 IEEE/ACIS 17th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016",
address = "United States",
}