Image signal-to-noise ratio estimation using Shape-Preserving Piecewise Cubic Hermite Autoregressive Moving Average model
Version of Record online: 9 JUL 2008
Copyright © 2008 Wiley-Liss, Inc.
Microscopy Research and Technique
Volume 71, Issue 10, pages 710–720, October 2008
How to Cite
Sim, K.S., Wee, M.Y. and Lim, W.K. (2008), Image signal-to-noise ratio estimation using Shape-Preserving Piecewise Cubic Hermite Autoregressive Moving Average model. Microsc. Res. Tech., 71: 710–720. doi: 10.1002/jemt.20610
- Issue online: 12 SEP 2008
- Version of Record online: 9 JUL 2008
- Manuscript Accepted: 10 APR 2008
- Manuscript Received: 12 JUN 2007
- electron microscope;
- signal-to-noise ratio;
- parameter estimation;
- autoregressive motion averaging 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, 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., 2008. © 2008 Wiley-Liss, Inc.