Abstract

Deblurring computed tomography (CT) images has been an active research topic in recent years because of the wide variety of challenges it offers. Hence, a novel filter is proposed in this article unveiling a simple, efficient, and fast deblurring process that involves few parameters, low calculations and does not utilize the undesirable iterative property or introduce the common deblurring problems. The newly proposed filter is validated on both real and synthetic blurred CT images to provide a sufficient understanding about its performance. Moreover, proper comparisons are made with high-profile deblurring methods, in which the results are evaluated using three reliable quality metrics of feature similarity index (FSIM), structural similarity (SSIM), and visual information fidelity in pixel domain (VIFP). The intensive experiments and performance evaluations exhibited the efficiency of the proposed filter, in that it outperformed all the comparative methods.

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