Water-to-Air Imaging: A Recovery Method for the Instantaneous Distorted Image Based on Structured Light and Local Approximate Registration

Abstract

Imaging through a continuously fluctuating water–air interface (WAI) is challenging. The image obtained in this way will suffer from complex refraction distortions that hinder the observer's accurate identification of the object. Reversing these distortions is an ill-posed problem, and the current restoration methods using high-resolution video streams are difficult to adapt to real-time observation scenarios. This paper proposes a method for restoring instantaneous distorted images based on structured light and local approximate registration. The scheme first uses structured light measurement technology to obtain the fluctuation information of the water surface. Then, the displacement information of the feature points on the distorted structured light image and the standard structured light image is obtained through the feature extraction algorithm and is used to estimate the distortion vector field of the corresponding sampling points in the distorted scene image. On this basis, the local approximate algorithm is used to reconstruct the distortion-free scene image. Experimental results show that the proposed algorithm can not only reduce image distortion and improve image visualization, but also has significantly better computational efficiency than other methods, achieving an “end-to-end” processing effect.