An adaptive interpolation and 3D reconstruction algorithm for underwater images

3D reconstruction technology is gradually applied to underwater scenes, which has become a crucial research direction for human ocean exploration and exploitation. However, due to the complexity of the underwater environment, the number of high-quality underwater images acquired by underwater robots is limited and cannot meet the requirements of 3D reconstruction. Therefore, this paper proposes an adaptive 3D reconstruction algorithm for underwater targets. We apply the frame interpolation technique to underwater 3D reconstruction, an unprecedented technical attempt. In this paper, we design a single-stage large-angle span underwater image interpolation model, which has an excellent enhancement effect on degraded underwater 2D images compared with other methods. Current methods make it challenging to balance the relationship between feature information acquisition and underwater image quality improvement. In this paper, an optimized cascaded feature pyramid scheme and an adaptive bidirectional optical flow estimation algorithm based on underwater NRIQA metrics are proposed and applied to the proposed model to solve the above problems. The intermediate image output from the model improves the image quality and retains the detailed information. Experiments show that the method proposed in this paper outperforms other methods when dealing with several typical degradation types of underwater images. In underwater 3D reconstruction, the intermediate image generated by the model is used as input instead of the degraded image to obtain a denser 3D point cloud and better visualization. Our method is instructive to the problem of acquiring underwater high-quality target images and underwater 3D reconstruction.