Department of Electrical and Computer Engineering, University of California, San Diego, La Jolla, CA 92093-0112, USA.
IEEE Trans Image Process. 2011 Nov;20(11):3097-111. doi: 10.1109/TIP.2011.2158229. Epub 2011 May 31.
This paper presents a fast algorithm for restoring video sequences. The proposed algorithm, as opposed to existing methods, does not consider video restoration as a sequence of image restoration problems. Rather, it treats a video sequence as a space-time volume and poses a space-time total variation regularization to enhance the smoothness of the solution. The optimization problem is solved by transforming the original unconstrained minimization problem to an equivalent constrained minimization problem. An augmented Lagrangian method is used to handle the constraints, and an alternating direction method is used to iteratively find solutions to the subproblems. The proposed algorithm has a wide range of applications, including video deblurring and denoising, video disparity refinement, and hot-air turbulence effect reduction.
本文提出了一种快速的视频序列恢复算法。与现有方法不同，所提出的算法不将视频恢复视为图像恢复问题的序列。相反，它将视频序列视为时空体，并提出时空全变差正则化以增强解的平滑度。通过将原始无约束最小化问题转换为等效的约束最小化问题来解决优化问题。使用增广拉格朗日方法来处理约束，并且交替方向方法用于迭代地找到子问题的解。所提出的算法有广泛的应用，包括视频去模糊和去噪、视频视差细化和热空气湍流效应减少。
