Abstract
Zhang & Karim's Laplacian-preprocessed detector [15] is robust against mis-identification of an image's thin-lines as impulse-noise-corrupted pixels. Wang & Zhang's "long-range correlation" denoising scheme [9] exploits any information-redundancy between an identified corrupted-pixel's local neighborhood with distant sub-images, to restore the corrupted pixel. This paper synergizes the above two algorithms, with the following algorithmic enhancements: (1) A pre-tuning of Zhang & Karim's threshold based on a rough estimation of the corrupting impulse-noise's spatial probability of occurrence, assuming the availability of a test-image "sufficiently" similar to the given corrupted image. (2) A new "difference-mean" criterion for better pixel-restoration. Limited simulations illustrate the above proposed scheme's efficacy and improvements.
| Original language | English |
|---|---|
| Pages (from-to) | 1569-1572 |
| Number of pages | 4 |
| Journal | Conference Record - Asilomar Conference on Signals, Systems and Computers |
| Volume | 2 |
| Publication status | Published - 1 Dec 2004 |
| Externally published | Yes |
| Event | Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers - Pacific Grove, CA, United States Duration: 7 Nov 2004 → 10 Nov 2004 |
Keywords
- Image matching
- Image processing
- Image restoration
- Impulse noise
- Median filters
- Nonlinear detection
- Shot noise
- Switched filters
ASJC Scopus subject areas
- General Engineering