WaterMamba: Visual State Space Model for Underwater Image Enhancement

arXiv:2405.08419v1 Announce Type: new
Abstract: Underwater imaging often suffers from low quality due to factors affecting light propagation and absorption in water. To improve image quality, some underwater image enhancement (UIE) methods based on convolutional neural networks (CNN) and Transformer have been proposed. However, CNN-based UIE methods are limited in modeling long-range dependencies, and Transformer-based methods involve a large number of parameters and complex self-attention mechanisms, posing efficiency challenges. Considering computational complexity and severe underwater image degradation, a state space …

abstract arxiv cnn convolutional convolutional neural networks cs.cv however image imaging light low modeling networks neural networks propagation quality space state state space model transformer type underwater visual water