Investigating numerical reconstruction quality and sparsity constraints on the holographic fringe pattern in digital holography

2017 ◽  
Author(s):  
Hyunwook Jeong ◽  
Hak Gu Kim ◽  
Yong Man Ro
Keyword(s):  
Digital Holography ◽  
Fringe Pattern ◽  
Numerical Reconstruction ◽  
Reconstruction Quality ◽  
Sparsity Constraints

scholarly journals Spatial Domain Terahertz Image Reconstruction Based on Dual Sparsity Constraints

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4116
Author(s):  
Xiaozhen Ren ◽  
Yuying Jiang
Keyword(s):  
Image Reconstruction ◽  
Optimization Problem ◽  
Separation Of Variables ◽  
Sampling Rate ◽  
Acquisition Time ◽  
Split Bregman ◽  
Edge Preserving ◽  
Reconstruction Quality ◽  
Sparsity Constraints ◽  
Reconstruction Model

Terahertz time domain spectroscopy imaging systems suffer from the problems of long image acquisition time and massive data processing. Reducing the sampling rate will lead to the degradation of the imaging reconstruction quality. To solve this issue, a novel terahertz imaging model, named the dual sparsity constraints terahertz image reconstruction model (DSC-THz), is proposed in this paper. DSC-THz fuses the sparsity constraints of the terahertz image in wavelet and gradient domains into the terahertz image reconstruction model. Differing from the conventional wavelet transform, we introduce a non-linear exponentiation transform into the shift invariant wavelet coefficients, which can amplify the significant coefficients and suppress the small ones. Simultaneously, the sparsity of the terahertz image in gradient domain is used to enhance the sparsity of the image, which has the advantage of edge preserving property. The split Bregman iteration scheme is utilized to tackle the optimization problem. By using the idea of separation of variables, the optimization problem is decomposed into subproblems to solve. Compared with the conventional single sparsity constraint terahertz image reconstruction model, the experiments verified that the proposed approach can achieve higher terahertz image reconstruction quality at low sampling rates.

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