Jian Bijian, Ma Chunbo, Zhu Dejian, Huang Qihong, Ao Jun
School of Information and Communication, Guilin University of Electronic Technology, Guilin 541000, China.
School of Artificial Intelligence, Hezhou University, Hezhou 542800, China.
Entropy (Basel). 2022 Dec 2;24(12):1765. doi: 10.3390/e24121765.
Imaging through the wavy water-air interface is challenging since the random fluctuations of water will cause complex geometric distortion and motion blur in the images, seriously affecting the effective identification of the monitored object. Considering the problems of image recovery accuracy and computational efficiency, an efficient reconstruction scheme that combines lucky-patch search and image registration technologies was proposed in this paper. Firstly, a high-quality reference frame is rebuilt using a lucky-patch search strategy. Then an iterative registration algorithm is employed to remove severe geometric distortions by registering warped frames to the reference frame. During the registration process, we integrate JADE and LBFGS algorithms as an optimization strategy to expedite the control parameter optimization process. Finally, the registered frames are refined using PCA and the lucky-patch search algorithm to remove residual distortions and random noise. Experimental results demonstrate that the proposed method significantly outperforms the state-of-the-art methods in terms of sharpness and contrast.
通过波浪起伏的水 - 空气界面进行成像具有挑战性，因为水的随机波动会在图像中引起复杂的几何失真和运动模糊，严重影响对被监测物体的有效识别。考虑到图像恢复精度和计算效率问题，本文提出了一种结合幸运补丁搜索和图像配准技术的高效重建方案。首先，使用幸运补丁搜索策略重建高质量参考帧。然后采用迭代配准算法，通过将扭曲帧与参考帧配准来消除严重的几何失真。在配准过程中，我们将JADE算法和LBFGS算法集成作为优化策略，以加速控制参数优化过程。最后，使用主成分分析（PCA）和幸运补丁搜索算法对配准后的帧进行细化，以消除残余失真和随机噪声。实验结果表明，所提出的方法在清晰度和对比度方面明显优于现有方法。
