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Bandlet-based sparsity regularization in video inpainting |
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| Affiliation: | 1. Department of Electrical and Computer Engineering, Concordia University, Montréal, QC H3G 2W1, Canada;2. Concordia Institute for Information Systems Engineering, Concordia University, Montréal, QC H3G 2W1, Canada;1. Beijing National Railway Research & Design Institute of Signal & Communication Co., Ltd, China;2. Department of Electronic Engineering, Tsinghua University, Beijing, China;3. Microsoft Research, Redmond, USA;1. Department of Electronic Engineering, The Chinese University of Hong Kong, Shatin N.T., Hong Kong;2. Hong Kong Applied Science and Technology Research Institute (ASTRI), Shatin N.T., Hong Kong |
| Abstract: | We present a bandlet-based framework for video inpainting in order to complete missing parts of a video sequence. The framework applies spatio-temporal geometric flows extracted by bandlets to reconstruct the missing data. First, a priority-based exemplar scheme enhanced by a bandlet-based patch fusion generates a preliminary inpainting result. Then, the inpainting task is completed by a 3D volume regularization algorithm which takes advantage of bandlet bases in exploiting the anisotropic regularities. The method does not need extra processes in order to satisfy visual consistency. The experimental results demonstrate the effectiveness of our proposed video completion technique. |
| Keywords: | Bandlets Inpainting Patch fusion Regularization Video completion Spatio-temporal flows Video sequence Missing information |
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