Robust image signal-to-noise ratio estimation using mixed Lagrange time delay estimation autoregressive model
A new technique based on the statistical autoregressive (AR) model has recently been developed as a solution to signal-to-noise (SNR) estimation in scanning electron microscope (SEM) images. In the present study, we propose to cascade the Lagrange time delay (LTD) estimator with the AR model. We cal...
| Main Authors: | , , |
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| Format: | Article |
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2004
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| Online Access: | http://shdl.mmu.edu.my/2432/ |
| _version_ | 1848790054690881536 |
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| author | Sim, , KS Chuah, , HT Cheng, , Z |
| author_facet | Sim, , KS Chuah, , HT Cheng, , Z |
| author_sort | Sim, , KS |
| building | MMU Institutional Repository |
| collection | Online Access |
| description | A new technique based on the statistical autoregressive (AR) model has recently been developed as a solution to signal-to-noise (SNR) estimation in scanning electron microscope (SEM) images. In the present study, we propose to cascade the Lagrange time delay (LTD) estimator with the AR model. We call this technique the mixed La-ran-e time delay estimation autoregressive (MLTDEAR) model. In a few test cases involving different images, this model is found to present an optimum solution for SNR estimation problems under different noise environments. In addition, it requires only a small filter order and has no noticeable estimation bias. The performance of the proposed estimator is compared with three existing methods: simple method, first-order linear interpolator, and AR-based estimator over several images. The efficiency of the MLTDEAR estimator, being more robust with noise, is significantly greater than that of the other three methods. |
| first_indexed | 2025-11-14T18:06:31Z |
| format | Article |
| id | mmu-2432 |
| institution | Multimedia University |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:06:31Z |
| publishDate | 2004 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | mmu-24322011-08-22T02:05:58Z http://shdl.mmu.edu.my/2432/ Robust image signal-to-noise ratio estimation using mixed Lagrange time delay estimation autoregressive model Sim, , KS Chuah, , HT Cheng, , Z TA Engineering (General). Civil engineering (General) A new technique based on the statistical autoregressive (AR) model has recently been developed as a solution to signal-to-noise (SNR) estimation in scanning electron microscope (SEM) images. In the present study, we propose to cascade the Lagrange time delay (LTD) estimator with the AR model. We call this technique the mixed La-ran-e time delay estimation autoregressive (MLTDEAR) model. In a few test cases involving different images, this model is found to present an optimum solution for SNR estimation problems under different noise environments. In addition, it requires only a small filter order and has no noticeable estimation bias. The performance of the proposed estimator is compared with three existing methods: simple method, first-order linear interpolator, and AR-based estimator over several images. The efficiency of the MLTDEAR estimator, being more robust with noise, is significantly greater than that of the other three methods. 2004-11 Article NonPeerReviewed Sim, , KS and Chuah, , HT and Cheng, , Z (2004) Robust image signal-to-noise ratio estimation using mixed Lagrange time delay estimation autoregressive model. SCANNING, 26 (6). pp. 287-295. ISSN 0161-0457 |
| spellingShingle | TA Engineering (General). Civil engineering (General) Sim, , KS Chuah, , HT Cheng, , Z Robust image signal-to-noise ratio estimation using mixed Lagrange time delay estimation autoregressive model |
| title | Robust image signal-to-noise ratio estimation using mixed Lagrange time delay estimation autoregressive model |
| title_full | Robust image signal-to-noise ratio estimation using mixed Lagrange time delay estimation autoregressive model |
| title_fullStr | Robust image signal-to-noise ratio estimation using mixed Lagrange time delay estimation autoregressive model |
| title_full_unstemmed | Robust image signal-to-noise ratio estimation using mixed Lagrange time delay estimation autoregressive model |
| title_short | Robust image signal-to-noise ratio estimation using mixed Lagrange time delay estimation autoregressive model |
| title_sort | robust image signal-to-noise ratio estimation using mixed lagrange time delay estimation autoregressive model |
| topic | TA Engineering (General). Civil engineering (General) |
| url | http://shdl.mmu.edu.my/2432/ |