[IPOL announce] new article: Implementation of a Denoising Algorithm Based on High-Order Singular Value Decomposition of Tensors

[announcements about the IPOL journal]

A new article is available in IPOL: http://www.ipol.im/pub/art/2019/226/

Fabien Feschet,
Implementation of a Denoising Algorithm Based on High-Order Singular 
Value Decomposition of Tensors,
Image Processing On Line, 9 (2019), pp. 158–182.
https://doi.org/10.5201/ipol.2019.226


Abstract
This article presents an implementation of a denoising algorithm based 
on High-Order Singular Value Decomposition (HOSVD) of tensors. It 
belongs to the class of patch-based methods such as BM3D and NL-Bayes. 
It exploits the grouping of similar patches in a local neighbourhood 
into a 3D matrix also called a third order tensor. Instead of performing 
different processing in different dimension, as in BM3D for instance, it 
is based on the decomposition of a tensor simultaneously in all 
dimensions reducing it to a core tensor in a similar way as SVD does for 
matrices in computing the diagonal matrix of singular values. The core 
tensor is filtered and a tensor is reconstructed by inverting the HOSVD. 
As common in patch-based algorithms, all tensors containing a pixel are 
then merged to produce an output image.