UWFormer: Underwater Image Enhancement via a Semi-Supervised Multi-Scale Transformer

arXiv:2310.20210v2 Announce Type: replace
Abstract: Underwater images often exhibit poor quality, distorted color balance and low contrast due to the complex and intricate interplay of light, water, and objects. Despite the significant contributions of previous underwater enhancement techniques, there exist several problems that demand further improvement: (i) The current deep learning methods rely on Convolutional Neural Networks (CNNs) that lack the multi-scale enhancement, and global perception field is also limited. (ii) The scarcity of paired real-world underwater datasets poses a …

abstract arxiv balance color contrast cs.cv current deep learning demand image images improvement light low objects quality scale semi-supervised transformer type underwater via water