An Image De-Noising Algorithm Based on the Dual-Tree Complex Wavelet

Yong Min Ning; Ling Ling Li; Hua Shi; Jing Chen

doi:10.4028/www.scientific.net/AMR.403-408.1412

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 403-408An Image De-Noising Algorithm Based on the...

An Image De-Noising Algorithm Based on the Dual-Tree Complex Wavelet

Abstract:

In this paper, an image de-noising algorithm based on the Dual-Tree Complex Wavelet Transform (DT-CWT) is proposed, which takes the advantage of redundant coefficients transformed by DT-CWT. The model of bivariate shrinkage function is used to provide a nonlinear threshold strategy. It exploits the dependency between inter-scale parents and children coefficients to recover the original coefficients more accurate. With the shift-invariance property of DT-CWT coefficients, the algorithm prevents the Gibbs effect caused by the thresholding, which further improves the reconstructed quality. Experiment results show that the de-noised image using DT-CWT can achieve more than 1dB prior to DWT with impressive visual results.

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Periodical:

Advanced Materials Research (Volumes 403-408)

Pages:

1412-1415

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.403-408.1412

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Online since:

November 2011

Authors:

Yong Min Ning, Ling Ling Li, Hua Shi, Jing Chen

Keywords:

Bivariate Shrinkage Function, Dual-Tree Complex Wavelet Transform, Image De-Noising, Shift-Invariance

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