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2021 | OriginalPaper | Chapter

21. Multidimensional Graphic Objects Filtration Using HoSVD Tensor Decomposition

Authors : Rumen Mironov, Ivo Draganov

Published in: New Approaches for Multidimensional Signal Processing

Publisher: Springer Singapore

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Abstract

A new approach for multidimensional graphic objects filtration using HoSVD tensor decomposition is presented. The experimental studies were performed on a set of test 3D images of size of 100 × 100 × 100, containing simple geometric objects—a sphere, a cylinder, a cone, etc. After that, Gaussian noise with different variation is added and the low-frequency part of the decomposition matrices U and S is filtered. The results obtained of the filtered images show that the quality of the restored images in the different planes and in total for the 3D image is excellent. The peak signal-to-noise ratio for different samples ranged from 28 to 50 dB.

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Metadata
Title
Multidimensional Graphic Objects Filtration Using HoSVD Tensor Decomposition
Authors
Rumen Mironov
Ivo Draganov
Copyright Year
2021
Publisher
Springer Singapore
DOI
https://doi.org/10.1007/978-981-33-4676-5_21