Halder Kalyan Kumar, Paul Manoranjan, Tahtali Murat, Anavatti Sreenatha G, Murshed Manzur
J Opt Soc Am A Opt Image Sci Vis. 2017 Apr 1;34(4):666-673. doi: 10.1364/JOSAA.34.000666.
In underwater imaging, water waves cause severe geometric distortions and blurring of the acquired short-exposure images. Corrections for these distortions have been tackled reasonably well by previous efforts but still need improvement in the estimation of pixel shift maps to increase restoration accuracy. This paper presents a new algorithm that efficiently estimates the shift maps from geometrically distorted video sequences and uses those maps to restore the sequences. A nonrigid image registration method is employed to estimate the shift maps of the distorted frames against a reference frame. The sharpest frame of the sequence, determined using a sharpness metric, is chosen as the reference frame. A k-means clustering technique is employed to discard too-blurry frames that could result in inaccuracy in the shift maps' estimation. The estimated pixel shift maps are processed to generate the accurate shift map that is used to dewarp the input frames into their nondistorted forms. The proposed method is applied on several synthetic and real-world video sequences, and the obtained results exhibit significant improvements over the state-of-the-art methods.
在水下成像中，水波会导致所采集的短曝光图像出现严重的几何失真和模糊。先前的努力已较好地解决了这些失真的校正问题，但在像素位移图的估计方面仍需改进，以提高恢复精度。本文提出了一种新算法，该算法能从几何失真的视频序列中高效地估计位移图，并利用这些图来恢复序列。采用非刚性图像配准方法来估计失真帧相对于参考帧的位移图。使用清晰度度量确定的序列中最清晰的帧被选作参考帧。采用k均值聚类技术来舍弃可能导致位移图估计不准确的过于模糊的帧。对估计出的像素位移图进行处理，以生成准确的位移图，该位移图用于将输入帧恢复为无失真的形式。将所提出的方法应用于多个合成和真实世界的视频序列，所获得的结果相较于现有方法有显著改进。
