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.