The blurring artefact may affect
the computed tomography images due to various real world limitations. Such
prevalent degradation is usually difficult to avert and it highly contributes
in concealing important medical information that already exists in the image.
As a consequence, the visual quality of the recorded images has been reduced
tremendously. Then, different deblurring concepts have been introduced toaddress this ill-posed problem. The drawbacks with many of the contemporary deblurring
methods are high complexity and processing times. Hence, a Gaussian prior
deconvolution is adopted in this study because of its ability to provide an
efficient and fast processing which is convenient for CT images. Intensive
tests have been conducted to attest the validity of this algorithm, for which
both naturally and synthetically degraded CT images are utilized. Furthermore,
the quality of the synthetic data is measured.