Soft Computing

, Volume 22, Issue 2, pp 635–644 | Cite as

Multichannel image denoising using color monogenic curvelet transform

Methodologies and Application
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Abstract

Color monogenic curvelet transform (CMCT) is a new multi-scale analysis tool for geometric image features. CMCT has useful properties that it behaves at the fine scales like curvelet transform and at the coarse scales like the color monogenic wavelet transform. CMCT has one magnitude and three phases which encode geometric information of color images. In order to demonstrate the properties of CMCT, new color image denoising algorithm is proposed based on CMCT and total variation. The experimental results demonstrate that the proposed algorithm is at par with or exceeds current state-of-the-art algorithms in both visual and quantitative performance.

Keywords

Curvelet transform Analytic signal Color monogenic wavelet transform Total variation Color image denoising 

Notes

Acknowledgments

This work is partially supported by National Natural Science Foundation of China under Grant No. (61563037); Natural Science Foundation of Jiangxi Province under Grant No. (20151BAB207031); Department of Education Science and Technology of Jiangxi Province under Grant No. (GJJ150755).

Compliance with ethical standards

Conflict of interest

The author Shan Gai in this paper declares no conflict of interest.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  1. 1.School of Information EngineeringNanchang Hangkong UniversityJiangxi NanchangPeople’s Republic of China

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