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

Citation

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

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Abstract

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.

Item Type: Article
Subjects: Q Science > Q Science (General)
Q Science > QH Natural history > QH301 Biology
Divisions: Faculty of Engineering and Technology (FET)
Depositing User: Ms Suzilawati Abu Samah
Date Deposited: 12 Sep 2011 03:47
Last Modified: 29 Dec 2020 06:42
URII: http://shdl.mmu.edu.my/id/eprint/2191

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