Abstract

We propose a method to improve the quality of the reconstructed images based on compressive sensing principles. The pseudo-inverse matrix and the total variation minimization algorithms are combined to reduce the sampling number of the computer generated hologram. Numerical simulations are performed and the results indicate that the peak signal to noise ratio is increased and the sampling ratio is decreased at the same time for holographic display.

© 2014 Chinese Optics Letters

Overview of compressive sensing techniques applied in holography [Invited]

Yair Rivenson, Adrian Stern, and Bahram Javidi
Appl. Opt. 52(1) A423-A432 (2013)

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)

Digital holographic phase imaging based on phase iteratively enhanced compressive sensing

Zhenpeng Luo, Jianshe Ma, Ping Su, and Liangcai Cao
Opt. Lett. 44(6) 1395-1398 (2019)

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)

On the performance of compressed sensing-based methods for millimeter-wave holographic imaging

Qiao Cheng, Akram Alomainy, and Yang Hao
Appl. Opt. 55(4) 728-738 (2016)