Improvement of image characteristics in high-voltage computed tomography (CT) by applying a compressed-sensing (CS)-based image deblurring scheme

We have established a high-voltage computed tomography (CT) system with a 1–3 MV LINAC x-ray generator for industrial nondestructive testing. However, reconstructed CT images are typically blurred, limiting its image performance, mainly due to the finite focal spot size of the x-ray source, aspects inherent to detector such as the detector pixel size and the detector resolution, and the reconstruction procedure as well. Thus the recovery of the reconstructed CT images from their degraded version is essential for improving the image characteristics. In this work, we investigated the compressed-sensing (CS)-based deconvolution scheme for more accurate image deblurring in CT. We implemented the proposed image deblurring algorithm for CT and performed a systematic simulation and experiment to demonstrate its viability. Our results indicate that the proposed deblurring scheme appears to be effective for the blurring problems in CT and is applicable to improve its present image characteristics.