Deep underwater image enhancement through colour cast removal and optimization algorithm

ABSTRACT

Blue–green colour cast effect and low contrast are common problems suffered by deep underwater images. This paper introduces a new method which consists of two major steps: red channel correction based on green and blue channels (RCCGB), and simultaneous contrast stretching and mean pixel enhancement (SCSMPE). The RCCGB is designed to minimize the effect of blue–green illumination. This step considers the differences between the red channel and other channels in terms of total pixel values. The second major step, SCSMPE is specifically designed to perform contrast stretching and improve the mean pixel value simultaneously through particle swarm optimization (PSO). Based on the visual observation, the proposed method significantly reduces the effect of the blue–green colour cast and improves the image contrast. Furthermore, the average quantitative values for 300 underwater images also demonstrate the superiority of the proposed method.

KEYWORDS:

• Underwater image processing
• colour correction
• blue–green colour cast
• contrast stretching
• particle swarm optimization

Acknowledgement

We thank all the reviewers for the comments and suggestions to improve this paper.

Disclosure statement

No potential conflict of interest was reported by the authors.

Notes on contributors

Kamil Zakwan Mohd Azmi received the B.Eng. degree in electrical engineering from Universiti Teknologi Malaysia, Malaysia, and the M.Eng. degree in electrical engineering from Universiti Malaysia Pahang, Malaysia. He is currently pursuing a Ph.D. degree with the Faculty of Manufacturing Engineering, Universiti Malaysia Pahang, Malaysia. His current interests include computational intelligence and image processing.

Ahmad Shahrizan Abdul Ghani received the M.Eng. degree in mechatronics from the University of Applied Sciences Augsburg, Germany, in 2009. He received the Ph.D. degree in image processing and computer vision system from Universiti Sains Malaysia, Malaysia in 2015. His current interests include colour image processing, computer vision system, and object tracking.

Zulkifli Md Yusof received the B.Sc. degree in electrical engineering from the University of Arizona, USA, and the M.Sc. degree in electrical engineering from Washington State University, USA, in 1989 and 1993, respectively. His research interests include computational intelligence and image processing.

Zuwairie Ibrahim received the B.Eng. degree in electrical engineering and the M.Eng. degree in image processing from Universiti Teknologi Malaysia, Malaysia, in 2000 and 2003, respectively. He received the Ph.D. degree in DNA computing from Meiji University, Japan in 2006. His research interests include computational intelligence and image processing.

Additional information

Funding

This work was supported by Universiti Malaysia Pahang (UMP) Internal Grant (RDU1803131) entitled ‘Development of Multi-Vision Guided Obstacle Avoidance System for Ground Vehicle.'