Parallel image dehazing algorithm based on GPU using fuzzy system and hybird evolution algorithm

Che Lun Hung; Ren You Yan; Hsiao Hsi Wang

doi:10.1109/SNPD.2016.7515962

Parallel image dehazing algorithm based on GPU using fuzzy system and hybird evolution algorithm

Che Lun Hung
, Ren You Yan
, Hsiao Hsi Wang

Providence University Taiwan

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

5 Scopus citations

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.

Original language	English
Title of host publication	2016 IEEE/ACIS 17th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016
Editors	Yihai Chen
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	581-583
Number of pages	3
ISBN (Electronic)	9781509022397
DOIs	https://doi.org/10.1109/SNPD.2016.7515962
State	Published - 18 07 2016
Externally published	Yes
Event	17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016 - Shanghai, China Duration: 30 05 2016 → 01 06 2016

Publication series

Name	2016 IEEE/ACIS 17th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016

Conference

Conference	17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016
Country/Territory	China
City	Shanghai
Period	30/05/16 → 01/06/16

Bibliographical note

Publisher Copyright:
© 2016 IEEE.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

CUDA
Evolution
GPU
Image Dehazing
Parallel Computing

Access to Document

10.1109/SNPD.2016.7515962

Cite this

Hung, C. L., Yan, R. Y., & Wang, H. H. (2016). Parallel image dehazing algorithm based on GPU using fuzzy system and hybird evolution algorithm. In Y. Chen (Ed.), 2016 IEEE/ACIS 17th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016 (pp. 581-583). Article 7515962 (2016 IEEE/ACIS 17th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SNPD.2016.7515962

Hung, Che Lun ; Yan, Ren You ; Wang, Hsiao Hsi. / Parallel image dehazing algorithm based on GPU using fuzzy system and hybird evolution algorithm. 2016 IEEE/ACIS 17th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016. editor / Yihai Chen. Institute of Electrical and Electronics Engineers Inc., 2016. pp. 581-583 (2016 IEEE/ACIS 17th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016).

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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.; 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016 ; Conference date: 30-05-2016 Through 01-06-2016",

year = "2016",

month = jul,

day = "18",

doi = "10.1109/SNPD.2016.7515962",

language = "英语",

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",

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Hung, CL, Yan, RY & Wang, HH 2016, Parallel image dehazing algorithm based on GPU using fuzzy system and hybird evolution algorithm. in Y Chen (ed.), 2016 IEEE/ACIS 17th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016., 7515962, 2016 IEEE/ACIS 17th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016, Institute of Electrical and Electronics Engineers Inc., pp. 581-583, 17th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016, Shanghai, China, 30/05/16. https://doi.org/10.1109/SNPD.2016.7515962

Parallel image dehazing algorithm based on GPU using fuzzy system and hybird evolution algorithm. / Hung, Che Lun; Yan, Ren You; Wang, Hsiao Hsi.
2016 IEEE/ACIS 17th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016. ed. / Yihai Chen. Institute of Electrical and Electronics Engineers Inc., 2016. p. 581-583 7515962 (2016 IEEE/ACIS 17th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AU - Hung, Che Lun

AU - Yan, Ren You

AU - Wang, Hsiao Hsi

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N2 - 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.

AB - 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.

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ER -

Hung CL, Yan RY, Wang HH. Parallel image dehazing algorithm based on GPU using fuzzy system and hybird evolution algorithm. In Chen Y, editor, 2016 IEEE/ACIS 17th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016. Institute of Electrical and Electronics Engineers Inc. 2016. p. 581-583. 7515962. (2016 IEEE/ACIS 17th International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing, SNPD 2016). doi: 10.1109/SNPD.2016.7515962

Parallel image dehazing algorithm based on GPU using fuzzy system and hybird evolution algorithm

Abstract

Publication series

Conference

Bibliographical note

UN SDGs

Keywords

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