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2017 | OriginalPaper | Chapter

A New Framework for Removing Impulse Noise in an Image

Authors : Zhou Yingyue, Xu Su, Zang Hongbin, He Hongsen

Published in: Image and Graphics

Publisher: Springer International Publishing

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Abstract

Nonlocal means filter (NLMF) or sparse representation based denoising technology has the remarkable performance in image denoising. In order to combine the advantages of the two methods together, a new image denoising framework is proposed. In this framework, the image containing impulse noise is processed firstly by NLMF to obtain a good temporary denoised image. Based on it, a number of patches are extracted for training a redundant dictionary which is adapted to the target signal. Finally, each noisy image patch in which the impulse noise is replaced by the values from the temporary denoised image is coded sparsely over the dictionary. Then, a clean image patch is reconstructed by multiplying the code efficient and the redundant dictionary. Verified by the extensive experiments, this denoising framework can not only obtain the better performance than that after use individually NLMF or sparse representation technology, but also get an obvious promotion in denoising texture images.

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Metadata
Title
A New Framework for Removing Impulse Noise in an Image
Authors
Zhou Yingyue
Xu Su
Zang Hongbin
He Hongsen
Copyright Year
2017
Book
Image and Graphics

Print ISBN: 978-3-319-71606-0

Electronic ISBN: 978-3-319-71607-7

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-319-71607-7_20

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