Abstract

We show an in-line digital holographic image reconstruction from subsampled holograms with resolution improvement and lensless magnification with high noise immunity by a compressive sensing approach. Our method treats the sensed field as subsampled, low-pass filtered and projected on a Fresnel–Bluestein base in an inverse problem approach to image reconstruction with controlled lensless magnification. So, we have demonstrated by simulation and experimental results that the approach can reconstruct images with quality even when used in holograms obtained from unusual subsampling schemes.

© 2020 Optical Society of America

Magnified reconstruction of digitally recorded holograms by Fresnel–Bluestein transform

John F. Restrepo and Jorge Garcia-Sucerquia
Appl. Opt. 49(33) 6430-6435 (2010)

Efficient compressive holographic reconstruction based on hologram segmentation

Xuelian Yu, Jiang Ban, Junjun Xiao, Xiufang Li, Kangwei Wang, Jiajing Yu, and Xingxu Bao
Appl. Opt. 60(31) 9844-9851 (2021)

Influence of sparse constraint functions on compressive holographic tomography

Da Sun, Zhenpeng Luo, Ping Su, Jianshe Ma, and Liangcai Cao
Appl. Opt. 60(4) A111-A119 (2021)

Preprocessing in digital lensless holographic microscopy for intensity reconstructions with enhanced contrast

Heberley Tobon, Carlos Trujillo, and Jorge Garcia-Sucerquia
Appl. Opt. 60(4) A215-A221 (2021)

Simulation of digital holographic recording and reconstruction using a generalized matrix method

Brad Bazow, Thuc Phan, Thanh Nguyen, Christopher Raub, and George Nehmetallah
Appl. Opt. 60(4) A21-A37 (2021)