Tensor/multi-dimensional array is a mathematical representation for multi-dimensional data, such as, multispectral image, hyperspectral image, multi-dimensional medical image and video. The related advances in applied mathematics allow us to gradually move from classical matrix based methods to tensor methods for image processing methods and applications. The resulted new research topic, called tensor image processing, offers new tools to exploit the multi-dimensional and intrinsic structures in multi-dimensional image data. In this inter-disciplinary research field, there are fast emerging works on tensor theory, tensor modeling, tensor based numerical analysis and computation, tensor optimization and applications on multi-dimensional image processing and analysis.

This special issue aims to collect the latest original contributions in tensor data processing, and offer new ideas, experiences and discussions by experts in this field. We encourage the submission of papers with new theory, analysis, methods, and applications in tensor data processing.

This is a special session of the 13th IEEE International Conference on Cyber, Physical and Social Computing (http://cse.stfx.ca/~cybermatics/2020/cpscom/index.php). Please submit your paper via the submission site (TBA) and select the special session of “Advances in Tensor Computation and Analysis for Image Processing” marked with “CPSComATCIP”.

Accepted conference papers will be published by IEEE (IEEE-DL and EI indexed). Selected papers, after further extensions and revisions, will be recommended to journal special issues. More details at the conference website:
http://cse.stfx.ca/~cybermatics/2020/cpscom/index.php

Potential topics include but are not limited to:

•     tensor computation
•     tensor data fusion
•     tensor rank-one approximation
•     Hankel tensor analysis and application
•     tensor data compression
•     tensor networks
•     tensor regression and classification
•     tensor decomposition
•     tensor-based feature matching

Session Chairs：
Hu Zhu, Nanjing University of Posts and Telecommunications, China
Guoxia Xu, The Chinese University of Hong Kong, Hong Kong