Reducing the Gaussian Blur Artifact from Ct Medical Images by Employing a Combination of Sharpening Filters and Iterative Deblurring Algorithms

Abstract

Obtained images through imaging systems are considered as degraded versions of the original view. Computed Tomography (CT) images have different types of degradations such as noise, blur and contrast imperfections. This paper handles the issue of deblurring CT medical images affected by Gaussian blur. Image deblurring is the procedure of decreasing the blur amount and grant the filtered image with an overall sharpened form. In this paper, the authors considered the Laplacian sharpening filter and the iterative Richardson – Lucy algorithm, and implemented a mixture of these two techniques to process the CT medical images. The suggested technique is applied to medical images that are synthetically and naturally degraded by blur. Moreover, an evaluation between the proposed combination and each employed technique is provided, along with the accuracy calculation using the universal image quality index (UIQI).

4 Figures and Tables

Cite this paper

@inproceedings{Sulong2012ReducingTG, title={Reducing the Gaussian Blur Artifact from Ct Medical Images by Employing a Combination of Sharpening Filters and Iterative Deblurring Algorithms}, author={Ghazali Bin Sulong}, year={2012} }