Hybrid framework for correcting water-to-air image sequences

When an underwater camera captures aerial targets, the received light undergoes refraction at the water-air interface. In particular, the calm water compresses the image, while turbulent water causes nonlinear distortion in the captured images. However, existing methods for correcting water-to-air distortion often cause images with distortion or overall shifts. To address the above issue, we propose a multi-strategy hybrid framework to process image sequences effectively, particularly for high-precision applications. Our framework includes a spatiotemporal crossover block to transform and merge features, effectively addressing the template-free problem. Additionally, we introduce an enhancement network to produce a high-quality template in the first stage and a histogram template method to maintain high chromaticity and reduce template noise in the correction stage. Furthermore, our framework incorporates a new registration scheme to facilitate sequence transfer and processing. Compared to existing algorithms, our approach achieves a high restoration level in terms of morphology and color for publicly available image sequences. (c) 2024 Optica Publishing Group. All rights, including for text and data mining (TDM), Artificial Intelligence (AI) training, and similar technologies, are reserved.