Asian Journal of Information Technology

Year: 2016
Volume: 15
Issue: 7
Page No. 1160 - 1165

A Hybrid Contourlet Transform for Deblurring and Denoising of Computer Tomography Images

Authors : A. Pasumpon Pandian, P. Rani and M. Indradevi

Abstract: Extraction of clinical information from medical images remains to be a challenging task till date as most of the images obtained from the imaging system are either corrupted by noise and blurring errors due to incorrect focus or motion capture. These image degradation factors influence the information extracted from them which bear a direct consequence on the diagnosis and treatment process. Image deblurring in presence of noise is a basically a tradeoff process as deblurring causes reduction of visual noise but at the same time can hide out essential information in the medical image. A multi resolution transform used in hybrid combination with Richard-Lucy algorithm to deblur the image and at the same time reduce the effect of noise on a CT image is proposed in this study. The filtering process is carried out in the Laplacian domain of the Contourlet transform. The utilization of the multi resolution approximation basically eliminates the need to determine any noise model. Experimental results show a clear improvement in the image quality.

How to cite this article:

A. Pasumpon Pandian, P. Rani and M. Indradevi, 2016. A Hybrid Contourlet Transform for Deblurring and Denoising of Computer Tomography Images. Asian Journal of Information Technology, 15: 1160-1165.

Design and power by Medwell Web Development Team. © Medwell Publishing 2022 All Rights Reserved