Breaking the Limitations with Sparse Inputs by Variational Frameworks (BLIss) in Terahertz Super-Resolution 3D Reconstruction

Demo MATLAB Code for Optica Optics Express (OE) Feature Issue 3D Image Acquisition and Display: Technology, Perception and Applications
Breaking the Limitations with Sparse Inputs by Variational Frameworks (BLIss) in Terahertz Super-Resolution 3D Reconstruction
Yiyao Zhang^1,2,3, Ke Chen^3,4, and Shang-Hua Yang^1,5

¹ Institute of Electronics Engineering, National Tsing Hua University, Hsinchu, 30013, Taiwan
² Department of Mathematical Sciences, University of Liverpool, Liverpool, L69 7ZL, UK
³ Centre for Mathematical Imaging Techniques, University of Liverpool, Liverpool, L69 7ZL, UK
⁴ Department of Mathematics and Statistics, University of Strathclyde, Glasgow, G1 1XH, UK
⁵ Department of Electrical Engineering, National Tsing Hua University, Hsinchu, 30013, Taiwan

by Yiyao Zhang [Yiyao.Zhang@liverpool.ac.uk; yiyaozhanguk@gmail.com]
Last Updated on 28/03/2024

Environment

Require MATLAB R2022a or later.

Developer [Version 1]
MATLAB R2024a, macOS Sonoma 14.2.1, Apple M1 Max Chip, and 64 GB Memory.

Usage

Run DATE20231220_BLIss_S37_ADMM.m
with input data BLIss_THzDeer_input.mat
and supplementary functions WE_ADMM_Formulation.p, Visual3D_BLIss.p
in the same directory.

Visualisation

Input

Results by Willmore, and Euler-Elastica Formulation