Multimedia Tools and Applications

, Volume 76, Issue 5, pp 6175–6188 | Cite as

Adaptive tensor compressive sensing based on noise estimation: application in three-dimensional images

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Abstract

Tensor Compressive Sensing (CS) is an emerging approach for higher order data representation, such as medical imaging, video sequences and multi-sensor networks. In this paper, we propose an Adaptive Tensor CS (ATCS) scheme for Three-dimensional (3D) images, especially those which contain noise. First, we find the relationship between reconstruction performance, noise level and sampling rate. Second, we develop the ATCS method by implementing a noise estimation algorithm. Finally, we apply the method in the CS system for efficient representation of 3D video sequences. We also demonstrate experimentally that ATCS outperforms other state of the art algorithms.

Keywords

Compressive sensing Low-rank tensor approximation Tucker decomposition 

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  1. 1.School of Information EngineeringNortheast Dianli UniversityJilinChina

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