[en] Image reconstruction in off-axis Terahertz digital holography is complicated due to the harsh recording conditions and the non-convexity form of the problem. In this paper, we propose an inverse problem-based reconstruction technique that jointly reconstructs the object field and the amplitude of the reference field. Regularization in the wavelet domain promotes a sparse object solution. A single objective function combining the data-fidelity and regularization terms is optimized with a dedicated algorithm based on an alternating direction method of multipliers framework. Each iteration alternates between two consecutive optimizations using projections operating on each solution and one soft thresholding operator applying to the object solution. The method is preceded by a windowing process to alleviate artifacts due to the mismatch between camera frame truncation and periodic boundary conditions assumed to implement convolution operators. Experiments demonstrate the effectiveness of the proposed method, in particular, improvements of reconstruction quality, compared to two other methods.
Research Center/Unit :
STAR - Space sciences, Technologies and Astrophysics Research - ULiège
Disciplines :
Mathematics Computer science
Author, co-author :
Kirkove, Murielle ; Université de Liège - ULiège > Centres généraux > CSL (Centre Spatial de Liège)
Zhao, Yuchen ; Université de Liège - ULiège > Centres généraux > CSL (Centre Spatial de Liège)
Leblanc, Olivier; UCL - Université Catholique de Louvain [BE] > ICTEAM Institute > ISPGroup, INMA
Jacques, Laurent; UCL - Université Catholique de Louvain [BE] > ICTEAM Institute > ISPGroup, INMA
Georges, Marc ; Université de Liège - ULiège > Centres généraux > CSL (Centre Spatial de Liège)
Language :
English
Title :
ADMM-inspired image reconstruction for Terahertz off-axis digital holography
Publication date :
08 December 2023
Journal title :
Journal of the Optical Society of America. A, Optics, Image Science, and Vision
FEDER - Fonds Européen de Développement Régional Région wallonne F.R.S.-FNRS - Fonds de la Recherche Scientifique
Funding text :
European Regional Development Fund/Wallonia region (2014-
2020 “En Mieux” program, project TERA4ALL), “Fonds de la Recherche
Scientifique – FNRS” (grant T.0136.20, project Learn2Sense).
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