Phaseformer: Phase-based Attention Mechanism for Underwater Image Restoration and Beyond

Autor:	Khan, MD Raqib, Negi, Anshul, Kulkarni, Ashutosh, Phutke, Shruti S., Vipparthi, Santosh Kumar, Murala, Subrahmanyam
Rok vydání:	2024
Předmět:	Computer Science - Computer Vision and Pattern Recognition Electrical Engineering and Systems Science - Image and Video Processing
Druh dokumentu:	Working Paper
Popis:	Quality degradation is observed in underwater images due to the effects of light refraction and absorption by water, leading to issues like color cast, haziness, and limited visibility. This degradation negatively affects the performance of autonomous underwater vehicles used in marine applications. To address these challenges, we propose a lightweight phase-based transformer network with 1.77M parameters for underwater image restoration (UIR). Our approach focuses on effectively extracting non-contaminated features using a phase-based self-attention mechanism. We also introduce an optimized phase attention block to restore structural information by propagating prominent attentive features from the input. We evaluate our method on both synthetic (UIEB, UFO-120) and real-world (UIEB, U45, UCCS, SQUID) underwater image datasets. Additionally, we demonstrate its effectiveness for low-light image enhancement using the LOL dataset. Through extensive ablation studies and comparative analysis, it is clear that the proposed approach outperforms existing state-of-the-art (SOTA) methods. Comment: 8 pages, 8 figures, conference
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2412.01456 Zobrazit plný text záznamu View this record from Arxiv