Please use this identifier to cite or link to this item: https://hdl.handle.net/2440/64727
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Type: Conference paper
Title: Image denoising by directional complex diffusion processes based on double-density dual-tree DWT
Author: Mao, C.
Shen, H.
Citation: Proceedings, 2010 3rd International Congress on Image and Signal Processing : CISP 2010, vol. 2 / Zheng-Hua Tan, Yi Wan, Tao Xiang, Yibin Song (eds.): pp. 698-702
Publisher: IEEE
Publisher Place: USA
Issue Date: 2010
ISBN: 9781424465163
Conference Name: International Congress on Image and Signal Processing (3rd : 2010 : Yantai, China)
Statement of
Responsibility: 
Cheng-lin Mao, Hong Shen
Abstract: Wavelet diffusion is a new popular image denoising method by combining the wavelet shrinkage and nonlinear diffusion. In this paper we extend the wavelet diffusion from real axis to complex domain and improve its performance. The double-density dual-tree discrete wavelet transform (DDDT-DWT) is a complex and directional transform. We propose an efficient image denoising algorithm by combining DDDT-DWT and the directional complex nonlinear diffusion process. We compute complex diffusion function based on directional complex wavelets. Experimental results show our algorithm is efficient.
Keywords: DDDT-DWT
complex wavelet transform
directional complex nonlinear diffusion
image denoising
wavelet diffusion
wavelet orientation
Rights: ©2010 IEEE
DOI: 10.1109/CISP.2010.5647203
Published version: http://dx.doi.org/10.1109/cisp.2010.5647203
Appears in Collections:Aurora harvest
Computer Science publications

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