NDLI: Ceramic microscopic image processing based on fast discrete curvelet transform

Content Provider	IEEE Xplore Digital Library
Author	Qing-Wu Li Guo-Gao Liu
Copyright Year	2007
Description	Author affiliation: Hohai Univ., Changzhou (Qing-Wu Li; Guo-Gao Liu)
Abstract	The properties of ceramic materials are strongly dependent on their microstructure. Ceramic microscopic image processing may be divided into two main procedures: image preprocessing for noise reduction to clarify the image and image segmentation for locating and detecting the objects of interest curvelet transform is a new extension to wavelet transform in two dimensions. Curvelet overcomes the limitation of wavelet in analyzing signals with dimension higher than 1D because it has the character of anisotropy. The fast discrete curvelet transform theory makes it understood and implemented more easily. A novel image denoising method is proposed in this paper. The nonlinear hyperbolic tangential function is selected as curvelet thresholding function. This denoising method is used to ceramic image processing. Firstly, the noisy ceramic image is denoised by the novel curvelet transform thresholding denoising method and then watershed algorithm is applied to the segmentation. Finally, the grain size distribution can be obtained from segmentation image. It has been proved that this method is effective for the ceramic microscopic image.
Starting Page	344
Ending Page	349
File Size	3038210
Page Count	6
File Format	PDF
ISBN	9781424410651
DOI	10.1109/ICWAPR.2007.4420691
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-11-02
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	threshold denoising Image processing Noise reduction Wavelet analysis Ceramics Discrete wavelet transforms Discrete transforms Image segmentation Microscopy Object detection curvelet transform Ceramic image segmentation Microstructure
Content Type	Text
Resource Type	Article

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