Asian Journal of Information Technology

Year: 2008
Volume: 7
Issue: 2
Page No. 53 - 57

A Multiscale Contourlet Transform Denoising Algorithm for X-ray Gastrointestinal Digital Image

Authors : Mi Deling , Feng Peng , Wei Biao , Liang Baimao , Peng Kexin and Ma Xiaoxin

Abstract: Although, X-ray gastrointestinal imaging system is a necessary medical diagnosis method, various noises will unavoidably appear in the image when X-ray gastrointestinal imaging is performed. An effective method to improve image quality is to reduce adverse effect on the image brought by noises, so as to de-noise X-ray gastrointestinal image. According to the features of X-ray gastrointestinal images with high resolution and complex details, Contourlet transform, which is capable of expressing high dimension geometry features such as image edges, details, etc., is used to propose an X-ray gastrointestinal image de-noising algorithm based on Multi-resolution Contourlet transform. This algorithm introduces cycle-spinning into de-noising process, thus, the "nick" problem brought by Contourlet transform hard threshold de-noising is overcome. Result shows that, for actual X-ray gastrointestinal image, this algorithm can both retain details in gastrointestinal images and obtain good de-noising effect and at the same time the calculation efficiency is high.

How to cite this article:

Mi Deling , Feng Peng , Wei Biao , Liang Baimao , Peng Kexin and Ma Xiaoxin , 2008. A Multiscale Contourlet Transform Denoising Algorithm for X-ray Gastrointestinal Digital Image. Asian Journal of Information Technology, 7: 53-57.

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