1 research outputs found
Tensor Completion through Total Variationwith Initialization from Weighted HOSVD
In our paper, we have studied the tensor completion problem when the sampling
pattern is deterministic. We first propose a simple but efficient weighted
HOSVD algorithm for recovery from noisy observations. Then we use the weighted
HOSVD result as an initialization for the total variation. We have proved the
accuracy of the weighted HOSVD algorithm from theoretical and numerical
perspectives. In the numerical simulation parts, we also showed that by using
the proposed initialization, the total variation algorithm can efficiently fill
the missing data for images and videos.Comment: 8 pages, 6 figures, ITA 202