Abstract

Compressive tomography consists of estimation of high-dimensional objects from lower dimensional measurements. We review compressive tomography using radiation fields, including geometric, wave, and statistical field models. We find coded apertures most appropriate for compressive coding with geometric models, spatial and frequency subsampling most appropriate for wave models, and temporal modulation most appropriate for statistical models. In each case, we show that compressive measurement enables snapshot 3D imaging, eliminating or reducing the need to sacrifice temporal resolution in multidimensional imaging.

© 2015 Optical Society of America

Compressed sampling strategies for tomography

Yan Kaganovsky, Daheng Li, Andrew Holmgren, HyungJu Jeon, Kenneth P. MacCabe, David G. Politte, Joseph A. O’Sullivan, Lawrence Carin, and David J. Brady
J. Opt. Soc. Am. A 31(7) 1369-1394 (2014)

Unified k-space theory of optical coherence tomography

Kevin C. Zhou, Ruobing Qian, Al-Hafeez Dhalla, Sina Farsiu, and Joseph A. Izatt
Adv. Opt. Photon. 13(2) 462-514 (2021)

Coding for compressive focal tomography

David J. Brady and Daniel L. Marks
Appl. Opt. 50(22) 4436-4449 (2011)

Deep learning for camera data acquisition, control, and image estimation

David J. Brady, Lu Fang, and Zhan Ma
Adv. Opt. Photon. 12(4) 787-846 (2020)

Structured illumination microscopy

Manish Saxena, Gangadhar Eluru, and Sai Siva Gorthi
Adv. Opt. Photon. 7(2) 241-275 (2015)