Adaptive Weighted Bregman Huber Total Variation Method for Terahertz Computed Tomography

To improve the image quality of terahertz (THz) continuous wave (CW) computed tomography (CT) under sparse-view projections, a sparse-view adaptive-weighted Bregman Huber total variation (AW-BHTV) method is proposed and experimentally evaluated at 0.11 THz. The Huber function is served as the fidelity term and TV function is worked for the regularization term, optimized by the adaptive weights, incorporating with iterative algorithms containing the modified simultaneous algebraic reconstruction technique (MSART) and the iterative filtered back-projection (FBP). Sparse-view reconstruction experiments are carefully implemented via polystyrene (PS) foam samples: Sample 1 and Sample 2, respectively. Under 20 projection angles by MSART based AW-BHTV, the values of rooted mean-square-error (RMSE), peak signal-to-noise ratio (PSNR), structure similarity (SSIM) and feature similarity (FSIM) are 0.0061, 22.1427, 0.8738 and 0.9902 for Sample 1 together with 0.0051, 22.9101, 0.8376 and 0.9885 for Sample 2 separately. All of the results above suggest that the proposed AW-BHTV method can effectively protect image details and strengthen image quality in sparse-view THz CW CT.