Abstract
This paper presents a novel approach to image denoising using adaptive principal components. Our assumptions are that the image is corrupted by additive white Gaussian noise. The new denoising technique performs well in terms of image visual fidelity, and in terms of PSNR values, the new technique compares very well against some of the most recently published denoising algorithms.
Keywords
Noise reductionVideo denoisingArtificial intelligenceNon-local meansImage denoisingComputer scienceFidelityPattern recognition (psychology)Additive white Gaussian noiseImage (mathematics)White noiseComputer visionNoise (video)Principal component analysisGaussian noiseVideo processing
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Publication Info
- Year
- 2004
- Type
- article
- Volume
- 1
- Pages
- I-101
- Citations
- 230
- Access
- Closed
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Cite This
D.D. Muresan,
T.W. Parks
(2004).
Adaptive principal components and image denoising.
, 1
, I-101.
https://doi.org/10.1109/icip.2003.1246908
Identifiers
- DOI
- 10.1109/icip.2003.1246908