目的 海上拍摄的视频存在大面积的无纹理区域,传统基于特征点检测和跟踪的视频去抖方法处理这类视频时往往效果较差。为此提出一种基于平稳光流估计的海上视频去抖算法。方法 该算法以层次化块匹配作为基础,引入平滑性约束计算基于层次块的光流,能够快速计算海上视频的近似光流场;然后利用基于平稳光流的能量函数优化,实现海上视频的高效去抖动。结果 分别进行了光流估计运行时间对比、视频稳定运行时间对比和用户体验比较共3组实验。相比于能处理海上视频去抖的SteadyFlow算法,本文的光流估计算法较SteadFlow算法的运动估计方法快10倍左右,整个视频去抖算法在处理速度上能提升70%以上。本文算法能够有效地实现海上视频去抖,获得稳定的输出视频。结论 提出了一种基于平稳光流估计的海上视频去抖算法,相对于传统方法,本文方法更适合处理海上视频的去抖。

Objective A marine video exhibits large-area textureless regions, and traditional video deshaking methods based on feature point detection and tracking for motion estimation usually have poor effects in processing such kinds of videos. In most marine videos captured in a ship, salient feature points are difficult to detect in regions of dominant water and sky, and the involved wave motions makes it difficult to track the detected few feature points. Thus, desirable deshaking results cannot be obtained by applying traditional video deshaking methods. Alternatively, this paper proposes a marine video deshaking method based on the estimation of steady optical flow or the SteadyFlow. Method The proposed algorithm is based on hierarchical block matching and integrating some smoothness constraints to compute the flow motion of the corresponding hierarchical blocks, thus facilitating rapid and accurate computation of the approximate optical flow field that exists in the marine video. The hierarchical blocks are typically organized into a pyramid with a few levels of blocks; in each level, the most matched blocks are searched in the neighborhood with the local smoothness constraints. The displacements of the blocks in the finest level form the optical flow motion of the marine video. Such motion estimation scheme is more suitable for a marine video with large regions of water and sky regions. Then, the estimated optical flow is smoothed in a spatially and temporally consistent manner to obtain a visually steady motion, where an energy functional optimization is applied to realize the efficient deshaking operation on the marine videos by using the steady optical flow. Result The SteadyFlow based marine video is implemented using the proposed deshaking algorithm; this is then tested on many marine video examples captured in a ship, which have obvious shakiness caused by wave motions. For the optical flow estimation, different methods on some public databases that have ground truth optical flow are compared for quantitative comparison. For the visual deshaking effect, a set of shaky marine videos are collected. Then, using such data, the proposed method is run along with other comparative methods and sophisticated software for further comparison. The user study is conducted to qualitatively evaluate the performances of all evaluated methods in terms of marine video deshaking. The experiment results on the running time statistics and visual quality comparison demonstrate that the proposed algorithm does not only efficiently realize marine video deshaking effects, but also accelerate the running speed of the process, thus reducing the timing by up to 70% of the traditional methods. Conclusion A video deshaking algorithm based on the steady optical flow estimation is proposed to deal with the particular set of marine videos. Compared with some traditional methods and software, the method proposed in this paper is more suitable for processing marine video shakiness because it can obtain more accurate motion estimation by using hierarchical block matching with smoothness constraints to compute the motion field of the marine videos.