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 ${\ell }_1$ norm. The algorithm is implemented on single moving object videos and color images for approximating the rank.

References in corpus (1)

• Canonical polyadic decomposition of third-order tensors: reduction to generalized eigenvalue decomposition