TY  - JOUR
T1  - A Hybrid Contourlet Transform for Deblurring and Denoising of Computer Tomography Images
AU - Pandian, A. Pasumpon AU - Rani, P. AU - Indradevi, M. 
JO  - Asian Journal of Information Technology
VL  - 15
IS  - 7
SP  - 1160
EP  - 1165
PY  - 2016
DA  - 2001/08/19
SN  - 1682-3915
DO  - ajit.2016.1160.1165
UR  - https://makhillpublications.co/view-article.php?doi=ajit.2016.1160.1165
KW  - Deblurring
KW  -denoising
KW  -multi resolution approximation
KW  -richard lucy algorithm
KW  -Point Spread Function (PSF)
AB  - 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.
ER  -