A Universal Noise Removal Algorithm with an Impulse Detector

Wenjie He, Roman Garnett, Timothy Huegerich, Charles Chui

Research output: Contribution to journalArticlepeer-review

Abstract

We introduce a local image statistic for identifying noise pixels in images corrupted with impulse noise of random values. The statistical values quantify how different in intensity the particular pixels are from their most similar neighbors. We continue to demonstrate how this statistic may be incorporated into a filter designed to remove
additive Gaussian noise. The result is a new filter capable of reducing both Gaussian and impulse noises from noisy images effectively, which performs remarkably well, both in terms of quantitative measures of signal restoration and qualitative judgements of image quality. Our approach is extended to automatically remove any mix of Gaussian
and impulse noise.
Original languageAmerican English
JournalIEEE Transactions on Image Processing
Volume14
StatePublished - 2005

Disciplines

  • Physical Sciences and Mathematics

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