Image Denoising Using Prethresholding Wiener Filtering
Rui Lü
Abstract
Rui Lü
Abstract
This paper introduces the statistical errors occurring in Wiener filtering and presents possibility of improv- ing Wiener filtering performance in image denoising using prethresholding as a processing step. The results obtained by standard Wiener filtering, inverse filtering and prethresholding Wiener filtering in degenerated image processing show that in image restoration standard Wiener filtering is better than inverse filtering and prethresholding Wiener is much better than both standard Wiener filtering and inverse filtering.
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This paper introduces the statistical errors occurring in Wiener filtering and presents possibility of improv- ing Wiener filtering performance in image denoising using prethresholding as a processing step. The results obtained by standard Wiener filtering, inverse filtering and prethresholding Wiener filtering in degenerated image processing show that in image restoration standard Wiener filtering is better than inverse filtering and prethresholding Wiener is much better than both standard Wiener filtering and inverse filtering.
Key concepts: Wiener filter, Wiener deconvolution, Computer science, Noise reduction, Inverse, Wiener process, Image (mathematics), Algorithm