A new standardisation and selection framework for real-time image dehazing algorithms from multi-foggy scenes based on fuzzy Delphi and hybrid multi-criteria decision analysis methods-Reference-Cited by-同舟云学术

A new standardisation and selection framework for real-time image dehazing algorithms from multi-foggy scenes based on fuzzy Delphi and hybrid multi-criteria decision analysis methods

Published:2020-05-26 Issue:4 Volume:33 Page:1029-1054
ISSN:0941-0643
Container-title:Neural Computing and Applications
language:en
Short-container-title:Neural Comput & Applic

Author:

Abdulkareem Karrar Hameed,Arbaiy Nureize,Zaidan A. A.,Zaidan B. B.,Albahri O. S.,Alsalem M. A.,Salih Mahmood M.

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence,Software

Link

https://link.springer.com/content/pdf/10.1007/s00521-020-05020-4.pdf

Reference184 articles.

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2. El Khoury J, Le Moan S, Thomas J-B, Mansouri A (2018) Color and sharpness assessment of single image dehazing. Multimed Tools Appl 77(12):15409–15430

3. Hu B, Li L, Liu H, Lin W, Qian J (2019) Pairwise-comparison-based rank learning for benchmarking image restoration algorithms. IEEE Trans Multimed 21(8):2042–2056

4. Zhu Q, Hu Z, Ivanov K (2015) Quantitative assessment mechanism transcending visual perceptual evaluation for image dehazing. In: 2015 IEEE international conference on robotics and biomimetics (ROBIO), 6–9 Dec 2015, pp 808–813. https://doi.org/10.1109/robio.2015.7418869

5. Hu ZY, Liu Q (2014) A method for dehazed image quality assessment. In: Wen Z, Li T (eds) Practical applications of intelligent systems, Iske 2013. Advances in intelligent systems and computing, vol 279, pp 909–913

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