Year: 2025
Type: article
Abstract: ABSTRACT We introduce the augmented total variation () regularization method for Radon‐type inverse problems. Our novel approach incorporates a dual variable into the regularization process, thereby extending and essentially augmenting traditional regularization techniques. The proposed method is robust, requiring only one algorithmic iteration to achieve accurate reconstructions. Numerical experiments on a modified Shepp–Logan phantom demonstrate that the augmented regularization consistently yields higher structural similarity index metric (SSIM) values and lower mean absolute difference (MAD) values compared to filtered backprojection and standard regularization. These findings indicate that our method not only reduces reconstruction errors but also preserves structural details.
Source: Studies in Applied Mathematics
DOI: 10.1111/sapm.70053
Institutions: Academy of Athens, National Technical University of Athens
Language: English
Subfield: Mathematical Physics
Field: Mathematics
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,550
OpenAlex ID: W4409563109