Image noise variance estimation using the mixed Lagrange time-delay autoregressive model

The mixed Lagrange time-delay estimation autoregressive (MLTDEAR) model is proposed as a solution to estimate image noise variance. The only information available to the proposed estimator is a corrupted image and the nature of additive white noise. The image autocorrelation function is calculated a...

Full description

Bibliographic Details
Main Authors: Sim, K.-S., Tso, C.-P., Law, K.-K.
Format: Article
Published: WILEY-LISS 2008
Subjects:
Online Access:http://shdl.mmu.edu.my/2751/
_version_ 1848790139770241024
author Sim, K.-S.
Tso, C.-P.
Law, K.-K.
author_facet Sim, K.-S.
Tso, C.-P.
Law, K.-K.
author_sort Sim, K.-S.
building MMU Institutional Repository
collection Online Access
description The mixed Lagrange time-delay estimation autoregressive (MLTDEAR) model is proposed as a solution to estimate image noise variance. The only information available to the proposed estimator is a corrupted image and the nature of additive white noise. The image autocorrelation function is calculated and used to obtain the MLTDEAR model coefficients; the relationship between the MLTDEAR and linear prediction models is utilized to estimate the model coefficients. The forward-backward prediction is then used to obtain the predictor coefficients; the MLTDEAR model coefficients and prior samples of zero-offset autocorrelation values are next used to predict the power of the noise-free image. Furthermore, the fundamental performance limit of the signal and noise estimation, as derived from the Cramer-Rao inequality, is presented.
first_indexed 2025-11-14T18:07:52Z
format Article
id mmu-2751
institution Multimedia University
institution_category Local University
last_indexed 2025-11-14T18:07:52Z
publishDate 2008
publisher WILEY-LISS
recordtype eprints
repository_type Digital Repository
spelling mmu-27512011-09-13T03:56:31Z http://shdl.mmu.edu.my/2751/ Image noise variance estimation using the mixed Lagrange time-delay autoregressive model Sim, K.-S. Tso, C.-P. Law, K.-K. T Technology (General) QA75.5-76.95 Electronic computers. Computer science The mixed Lagrange time-delay estimation autoregressive (MLTDEAR) model is proposed as a solution to estimate image noise variance. The only information available to the proposed estimator is a corrupted image and the nature of additive white noise. The image autocorrelation function is calculated and used to obtain the MLTDEAR model coefficients; the relationship between the MLTDEAR and linear prediction models is utilized to estimate the model coefficients. The forward-backward prediction is then used to obtain the predictor coefficients; the MLTDEAR model coefficients and prior samples of zero-offset autocorrelation values are next used to predict the power of the noise-free image. Furthermore, the fundamental performance limit of the signal and noise estimation, as derived from the Cramer-Rao inequality, is presented. WILEY-LISS 2008-04 Article NonPeerReviewed Sim, K.-S. and Tso, C.-P. and Law, K.-K. (2008) Image noise variance estimation using the mixed Lagrange time-delay autoregressive model. Microscopy Research and Technique, 71 (4). pp. 315-324. ISSN 1059910X http://dx.doi.org/10.1002/jemt.20558 doi:10.1002/jemt.20558 doi:10.1002/jemt.20558
spellingShingle T Technology (General)
QA75.5-76.95 Electronic computers. Computer science
Sim, K.-S.
Tso, C.-P.
Law, K.-K.
Image noise variance estimation using the mixed Lagrange time-delay autoregressive model
title Image noise variance estimation using the mixed Lagrange time-delay autoregressive model
title_full Image noise variance estimation using the mixed Lagrange time-delay autoregressive model
title_fullStr Image noise variance estimation using the mixed Lagrange time-delay autoregressive model
title_full_unstemmed Image noise variance estimation using the mixed Lagrange time-delay autoregressive model
title_short Image noise variance estimation using the mixed Lagrange time-delay autoregressive model
title_sort image noise variance estimation using the mixed lagrange time-delay autoregressive model
topic T Technology (General)
QA75.5-76.95 Electronic computers. Computer science
url http://shdl.mmu.edu.my/2751/
http://shdl.mmu.edu.my/2751/
http://shdl.mmu.edu.my/2751/