Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/22213
Title: Nonlinear curvelet diffusion for noisy image enhancement
Authors: Li, Y
Ning, H
Zhang, Y
Feng, D
Keywords: Denoising
Image enhancement
Mirror-extended curvelet transform
Nonlinear diffusion
Issue Date: 2011
Publisher: IEEE
Source: 2011 18th IEEE International Conference on Image Processing (ICIP), 11-14 September 2011, Brussels, p. 2557-2560 How to cite?
Abstract: Digital image degradation normally arises during image acquisition and processing, which has a direct influence on the visual quality of the image. This paper proposes a combined method for enhancement of noisy image by using the mirror-extended curvelet transform and nonlinear anisotropic diffusion. First, an improved enhancement function is proposed to nonlinearly shrink and stretch the curvelet coefficients. Then, the enhanced results are further processed by the nonlinear diffusion where only the nonsignificant, i.e., nonthresholded, curvelet coefficients are changed by means of a diffusion process in order to reduce the pseudo-Gibbs artifacts. Experimental results indicate the proposed method has better performances to enhance the shape of edges and important detailed features as well as suppress noise, in comparison to the curvelet-based enhancement method without diffusion and the wavelet-based enhancement methods with/without diffusion.
URI: http://hdl.handle.net/10397/22213
ISBN: 978-1-4577-1304-0
978-1-4577-1302-6 (E-ISBN)
ISSN: 1522-4880
DOI: 10.1109/ICIP.2011.6116185
Appears in Collections:Conference Paper

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