Reconstruction of underwater images with distortion using robust image registration
Yang Xu, Zhen Zhang · 2019
When imaging through an undulating clear water surface, a complex series of refractions and reflections occur throughout the imaging path, and light rays are bent by unknown amounts. So the captured images usually contain severe geometric distortions. In this paper, an iterative robust registration algorithm is employed to remove the distortions in frames by registering each frame to a reference image. As the traditional image registration algorithm is impeded by the severely blur mean, we decide to reconstruct a high quality reference as the surrogate of the mean. We first select the image patches with higher quality from the distorted sequence to reconstruct a single image. In the patches selection process, the image quality of patches is evaluated from sharpness and geometric distortion. Then the blind deconvolution technique is employed to deblur the image, which will be used as a reference of the next registration process. Experiment shows that the proposed algorithm performs well in restoring the distorted underwater images and has less computational time than the state-of-the-art method.