A hybrid algorithm for underwater image restoration based on color correction and image sharpening

• Published in: Multimedia systems 2022-12, Vol.28 (6), p.1975-1985
• Main Authors: Meng, Haiyang, Yan, Yongjie, Cai, Chengtao, Qiao, Renjie, Wang, Feng
• Format: Article
• Language: English
• Subjects: Algorithms; Balancing; Channels; Color; Computer Communication Networks; Computer Graphics; Computer Science; Cryptology; Data Storage Representation; Deep Learning Methods for Cyber-bullying Detection in Multi-modal Data; Image enhancement; Image restoration; Multimedia Information Systems; Operating Systems; Special Issue Paper; Underwater; Visibility
• ISSN: 0942-4962; 1432-1882
• DOI: 10.1007/s00530-020-00693-2

In this paper, an effective method is proposed for restoring underwater image based on color correction and image sharpening. The main purpose of this method is to improve the visibility of underwater images. Traditional methods generally adopt color balancing method to restore the images. However, we found that color balancing has a poor effectiveness on underwater image when the values of blue channel are greater than other two channels, specially, red channel is great of small than blue channel. Therefore, we propose a hybrid method for color correction process based on a principle that exploits the relationship of three channels (red channel, green channel, and blue channel). On the other words, color balancing will be employed to restore the images when the values of red channel approximate to blue channel, while the DCP-base method will be used if otherwise. To enhance the sharpness of underwater image, we employed a sharpening process based on Maximum a Posteriori (MAP) method when color correction has finished. The proposed method also been validated through carrying out experiments on several underwater image datasets which are provided by previous researchers. Our validation has proved that the proposed method has a better performance than the state-of-the-art methods.