NDLI: Fast tensor signal filtering using fixed point algorithm

Content Provider	IEEE Xplore Digital Library
Author	Marot, J. Bourennane, S.
Copyright Year	2008
Description	Author affiliation: Inst. Fresnel, Marseille (Marot, J.; Bourennane, S.)
Abstract	Subspace-based methods rely on the selection of leading eigenvectors, associated with dominant eigenvalues. They have been extended to tensor data processing, such as denoising. Usually EVD (eigenvalue decomposition) is performed and data projection on leading eigenvectors results in noise reduction. Tensor processing methods, in particular multiway Wiener filtering algorithm, include an ALS (alternating least squares) loop, which involves several EVDs. Fixed point algorithm is a faster method than EVD to estimate a fixed number of eigenvectors. In this paper, we adapt fixed point algorithm to the estimation of only the required leading eigenvectors in a tensor processing framework. We adapt inverse power method to estimate the required noise variance. We provide a comparative study in terms of speed through an application to hyperspectral image denoising.
Starting Page	921
Ending Page	924
File Size	257113
Page Count	4
File Format	PDF
ISBN	9781424414833
ISSN	15206149
DOI	10.1109/ICASSP.2008.4517761
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-03-31
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Tensile stress Filtering algorithms Signal processing algorithms Wiener filter Noise reduction Multidimensional systems Eigenvalues and eigenfunctions Least squares methods Hyperspectral imaging Noise measurement Image restoration Algebra Algorithms Multidimensional signal processing Wiener filtering
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Nonorthogonal Tensor Matricization for Hyperspectral Image Filtering

Fast subspace-based tensor data filtering

Noise Removal From Hyperspectral Images by Multidimensional Filtering

Multidimensional wiener filtering using fourth order statistics of hyperspectral images

Hyperspectral image denoising with rare signal preserving by jointly filtering image component

Improvement of Classification for Hyperspectral Images Based on Tensor Modeling

A fast convergence median LMS algorithm

Fast algorithms for 2-D least squares FIR filtering

Adaptive Flattening for Multidimensional Image Restoration

Fast tensor signal filtering using fixed point algorithm

Similar Documents

Nonorthogonal Tensor Matricization for Hyperspectral Image Filtering

Fast subspace-based tensor data filtering

Noise Removal From Hyperspectral Images by Multidimensional Filtering

Multidimensional wiener filtering using fourth order statistics of hyperspectral images

Hyperspectral image denoising with rare signal preserving by jointly filtering image component

Improvement of Classification for Hyperspectral Images Based on Tensor Modeling

A fast convergence median LMS algorithm

Fast algorithms for 2-D least squares FIR filtering

Adaptive Flattening for Multidimensional Image Restoration

Fast tensor signal filtering using fixed point algorithm