Imaging through a time-varying water surface exhibits severe non-rigid geometric distortions and motion blur. Theoretically, although the water surface possesses smoothness and temporal periodicity, random fluctuations are inevitable in an actual video sequence. Meanwhile, considering the distribution of information, the image structure contributes more to the restoration. In this paper, a new two-stage restoration method for distorted underwater video sequences is presented. During the first stage, salient feature points, which are selected through multiple methods, are tracked across the frames, and the motion fields at all pixels are estimated using a compressive sensing solver to remove the periodic distortions. During the second stage, the combination of a guided filter algorithm and an image registration method is applied to remove the structural-information-oriented residual distortions. Finally, the experiment results show that the method outperforms other state-of-the-art approaches in terms of the recovery effect and time.
The full text can be downloaded at https://link.springer.com/article/10.1007/s40436-020-00340-z
Zhen Zhang
,
Yu-Gui Tang
,
Kuo Yang
. A two-stage restoration of distorted underwater images using compressive sensing and image registration[J]. Advances in Manufacturing, 2021
, 9(2)
: 273
-285
.
DOI: 10.1007/s40436-020-00340-z
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