TY  - JOUR
T1  - A Multiscale Contourlet Transform Denoising Algorithm for X-ray Gastrointestinal Digital Image
AU - , Mi Deling AU - , Feng Peng AU - , Wei Biao AU - , Liang Baimao AU - , Peng Kexin AU - , Ma Xiaoxin 
JO  - Asian Journal of Information Technology
VL  - 7
IS  - 2
SP  - 53
EP  - 57
PY  - 2008
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2008.53.57
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2008.53.57
KW  - X-ray gastrointestinal image
KW  -multi-scale geometric analysis
KW  -contourlet transform
KW  -cycle spinning
AB  - 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.
ER  -