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An automated approach to quasi-periodic noise removal in natural images

Frédéric Sur 1 Michel Grediac 2
1 MAGRIT - Visual Augmentation of Complex Environments
LORIA - ALGO - Department of Algorithms, Computation, Image and Geometry, Inria Nancy - Grand Est
Abstract : Quasi-periodic noise may affect digital images. This phenomenon is reflected by spurious repetitive patterns covering the whole image. Quasi-periodic noise is by nature well localized in the Fourier spectrum. A possibility is thus to attenuate it through a well-designed notch filter. In contrast to existing algorithms which require hand-tuned filter design, this research report presents an automated approach based on the expected power spectrum of a natural image. The resulting algorithm enables to eliminate a large range of repetitive structures, from simple periodic noises, whose influence on the image spectrum is limited to a few Fourier coefficients, to quasi-periodic noises with much more complex spectrum structures. The proposed algorithm is assessed on the basis of various experiments. A comparison with morphological component analysis (MCA), a blind source separation algorithm, is also provided. A Matlab implementation is available. This report is an extension of a published article.
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Submitted on : Monday, January 5, 2015 - 1:11:20 PM
Last modification on : Saturday, October 16, 2021 - 11:26:07 AM
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  • HAL Id : hal-01099795, version 1


Frédéric Sur, Michel Grediac. An automated approach to quasi-periodic noise removal in natural images. [Research Report] RR-8660, INRIA Nancy, équipe Magrit; Institut Pascal, Université Blaise Pascal; INRIA. 2015. ⟨hal-01099795⟩



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