Image signal-to-noise ratio estimation using Shape-Preserving Piecewise Cubic Hermite Autoregressive Moving Average model

We propose to cascade the Shape-Preserving Piecewise Cubic Hermite model with the Autoregressive Moving Average (ARMA) interpolator; we call this technique the Shape-Preserving Piecewise Cubic Hermite Autoregressive Moving Average (SP2CHARMA) model. In a few test cases involving different images, th...

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Main Authors: Sim, Kok Swee, Wee, M. Y., LIM, W. K.
Format: Article
Published: WILEY-LISS, DIV JOHN WILEY & SONS INC 2008
Subjects:
Online Access:http://shdl.mmu.edu.my/2191/
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author Sim, Kok Swee
Wee, M. Y.
LIM, W. K.
author_facet Sim, Kok Swee
Wee, M. Y.
LIM, W. K.
author_sort Sim, Kok Swee
building MMU Institutional Repository
collection Online Access
description We propose to cascade the Shape-Preserving Piecewise Cubic Hermite model with the Autoregressive Moving Average (ARMA) interpolator; we call this technique the Shape-Preserving Piecewise Cubic Hermite Autoregressive Moving Average (SP2CHARMA) model. In a few test cases involving different images, this model is found to deliver an optimum solution for signal to noise ratio (SNR) estimation problems under different noise environments. The performance of the proposed estimator is compared with two existing methods: the autoregressive-based and autoregressive moving average estimators. Being more robust with noise, the SP2CHARMA. estimator has efficiency that is significantly greater than those of the two methods. Microsc. Res. Tech. 71:710-720, 2008. (C) 2008 Wiley-Liss, Inc.
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spelling mmu-21912020-12-29T06:42:31Z http://shdl.mmu.edu.my/2191/ Image signal-to-noise ratio estimation using Shape-Preserving Piecewise Cubic Hermite Autoregressive Moving Average model Sim, Kok Swee Wee, M. Y. LIM, W. K. Q Science (General) QH301 Biology We propose to cascade the Shape-Preserving Piecewise Cubic Hermite model with the Autoregressive Moving Average (ARMA) interpolator; we call this technique the Shape-Preserving Piecewise Cubic Hermite Autoregressive Moving Average (SP2CHARMA) model. In a few test cases involving different images, this model is found to deliver an optimum solution for signal to noise ratio (SNR) estimation problems under different noise environments. The performance of the proposed estimator is compared with two existing methods: the autoregressive-based and autoregressive moving average estimators. Being more robust with noise, the SP2CHARMA. estimator has efficiency that is significantly greater than those of the two methods. Microsc. Res. Tech. 71:710-720, 2008. (C) 2008 Wiley-Liss, Inc. WILEY-LISS, DIV JOHN WILEY & SONS INC 2008-10 Article NonPeerReviewed Sim, Kok Swee and Wee, M. Y. and LIM, W. K. (2008) Image signal-to-noise ratio estimation using Shape-Preserving Piecewise Cubic Hermite Autoregressive Moving Average model. Microscopy Research and Technique, 71 (10). pp. 710-720. ISSN 1059910X http://dx.doi.org/10.1002/jemt.20610 doi:10.1002/jemt.20610 doi:10.1002/jemt.20610
spellingShingle Q Science (General)
QH301 Biology
Sim, Kok Swee
Wee, M. Y.
LIM, W. K.
Image signal-to-noise ratio estimation using Shape-Preserving Piecewise Cubic Hermite Autoregressive Moving Average model
title Image signal-to-noise ratio estimation using Shape-Preserving Piecewise Cubic Hermite Autoregressive Moving Average model
title_full Image signal-to-noise ratio estimation using Shape-Preserving Piecewise Cubic Hermite Autoregressive Moving Average model
title_fullStr Image signal-to-noise ratio estimation using Shape-Preserving Piecewise Cubic Hermite Autoregressive Moving Average model
title_full_unstemmed Image signal-to-noise ratio estimation using Shape-Preserving Piecewise Cubic Hermite Autoregressive Moving Average model
title_short Image signal-to-noise ratio estimation using Shape-Preserving Piecewise Cubic Hermite Autoregressive Moving Average model
title_sort image signal-to-noise ratio estimation using shape-preserving piecewise cubic hermite autoregressive moving average model
topic Q Science (General)
QH301 Biology
url http://shdl.mmu.edu.my/2191/
http://shdl.mmu.edu.my/2191/
http://shdl.mmu.edu.my/2191/