Image Denoising Based on Hybrid Fourier and Neighborhood Wavelet Coefficients

DOI

10.2991/emeit.2012.500How to use a DOI?

Keywords

image denoising, Fourier transform, neighboring wavelet coefficients, PSNR

Abstract

Image denoising is a classical topic and a difficult problem in the field of image processing. Fourier transform can effectively sparsely represent the smoothing texture part of the image, but can’t effectively represent mutations in the image. The wavelet transform can sparsely represent sharply changing parts in the image, but can’t effectively represent the texture and the slowly changing parts of the image. A new method based on hybrid Fourier and neighborhood wavelet coefficient is presented, and experiments show that the method is valid and can improve the visual effect, and that the objective indicator PSNR is better than NeightShrink method.

Copyright

© 2012, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jun Cheng
AU  - Songli Lei
PY  - 2012/09
DA  - 2012/09
TI  - Image Denoising Based on Hybrid Fourier and Neighborhood Wavelet Coefficients
BT  - Proceedings of the 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT 2012)
PB  - Atlantis Press
SP  - 2258
EP  - 2262
SN  - 1951-6851
UR  - https://doi.org/10.2991/emeit.2012.500
DO  - 10.2991/emeit.2012.500
ID  - Cheng2012/09
ER  -