SE–RWNN: an synergistic evolution and randomly wired neural network‐based model for adaptive underwater image enhancement

Author:

Li Yang1ORCID,Chen Rong1

Affiliation:

1. College of Information Science and TechnologyDalian Maritime UniversityDalianPeople's Republic of China

Funder

National Natural Science Foundation of China

Fundamental Research Funds for the Central Universities

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Reference55 articles.

1. An Augmented Reality Application to Assist Teleoperation of Underwater Manipulators

2. Advances in Underwater Robot Vehicles for Deep Ocean Exploration: Navigation, Control, and Survey Operations

3. Camus T.A. Salganicoff M. Chmielewski T.A. Jr. et al.: ‘Method and apparatus for removal of bright or dark spots by the fusion of multiple images’ 2000 US Patent 6 088 470

4. Narasimhan S.G. Nayar S.K.: ‘Shedding light on the weather’.Proc. 2003 IEEE Computer Society Conf. on Computer Vision and Pattern Recognition 2003 Madison WI USA vol. 1 2003 pp.I–I

5. Yang H.‐Y. Chen P.‐Y. Huang C.‐C. et al.: ‘Low complexity underwater image enhancement based on dark channel prior’.2011 Second Int. Conf. on Innovations in Bio‐inspired Computing and Applications Shenzhen People's Republic of China 2011 pp.17–20

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