Image signal-to-noise ratio estimation using the autoregressive model
In the last two decades, a variety of techniques for signal-to-noise ratio (SNR) estimation in scanning electron microscope (SEM) images have been proposed. However, these techniques can be divided into two groups: first, SNR estimators of good accuracy, but based on impractical assumptions; second,...
| Main Authors: | , |
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| Format: | Article |
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2004
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| Online Access: | http://shdl.mmu.edu.my/2476/ |
| _version_ | 1848790064737288192 |
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| author | Sim, , KS Kamel,, NS |
| author_facet | Sim, , KS Kamel,, NS |
| author_sort | Sim, , KS |
| building | MMU Institutional Repository |
| collection | Online Access |
| description | In the last two decades, a variety of techniques for signal-to-noise ratio (SNR) estimation in scanning electron microscope (SEM) images have been proposed. However, these techniques can be divided into two groups: first, SNR estimators of good accuracy, but based on impractical assumptions; second, estimators based on realistic assumptions but of poor accuracy. In this paper we propose the implementation of autoregressive (AR)-model interpolation as a solution to the problem. Unlike others, the proposed technique is based on a single SEM image and offers the required accuracy and robustness in estimating SNR values. |
| first_indexed | 2025-11-14T18:06:41Z |
| format | Article |
| id | mmu-2476 |
| institution | Multimedia University |
| institution_category | Local University |
| last_indexed | 2025-11-14T18:06:41Z |
| publishDate | 2004 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | mmu-24762011-08-22T01:57:55Z http://shdl.mmu.edu.my/2476/ Image signal-to-noise ratio estimation using the autoregressive model Sim, , KS Kamel,, NS TA Engineering (General). Civil engineering (General) In the last two decades, a variety of techniques for signal-to-noise ratio (SNR) estimation in scanning electron microscope (SEM) images have been proposed. However, these techniques can be divided into two groups: first, SNR estimators of good accuracy, but based on impractical assumptions; second, estimators based on realistic assumptions but of poor accuracy. In this paper we propose the implementation of autoregressive (AR)-model interpolation as a solution to the problem. Unlike others, the proposed technique is based on a single SEM image and offers the required accuracy and robustness in estimating SNR values. 2004-05 Article NonPeerReviewed Sim, , KS and Kamel,, NS (2004) Image signal-to-noise ratio estimation using the autoregressive model. SCANNING , 26 (3). pp. 135-139. ISSN 0161-0457 |
| spellingShingle | TA Engineering (General). Civil engineering (General) Sim, , KS Kamel,, NS Image signal-to-noise ratio estimation using the autoregressive model |
| title | Image signal-to-noise ratio estimation using the autoregressive model |
| title_full | Image signal-to-noise ratio estimation using the autoregressive model |
| title_fullStr | Image signal-to-noise ratio estimation using the autoregressive model |
| title_full_unstemmed | Image signal-to-noise ratio estimation using the autoregressive model |
| title_short | Image signal-to-noise ratio estimation using the autoregressive model |
| title_sort | image signal-to-noise ratio estimation using the autoregressive model |
| topic | TA Engineering (General). Civil engineering (General) |
| url | http://shdl.mmu.edu.my/2476/ |