Rank Approximation of a Tensor with Applications in Color Image and Video Processing
Abstract
We propose a block coordinate descent type algorithm for estimating the rank of a given tensor. In addition, the algorithm provides the canonical polyadic decomposition of a tensor. In order to estimate the tensor rank we use sparse optimization method using 1 norm. The algorithm is implemented on single moving object videos and color images for approximating the rank.
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