@inproceedings{420b46f417d34cda82531ac316d2ca53,
title = "3PointTM: Faster Measurement of High-Dimensional Transmission Matrices",
abstract = "A transmission matrix (TM) describes the linear relationship between input and output phasor fields when a coherent wave passes through a scattering medium. Measurement of the TM enables numerous applications, but is challenging and time-intensive for an arbitrary medium. State-of-the-art methods, including phase-shifting holography and double phase retrieval, require significant amounts of measurements, and post-capture reconstruction that is often computationally intensive. In this paper, we propose 3PointTM, an approach for sensing TMs that uses a minimal number of measurements per pixel—reducing the measurement budget by a factor of two as compared to state of the art in phase-shifting holography for measuring TMs—and has a low computational complexity as compared to phase retrieval. We validate our approach on real and simulated data, and show successful focusing of light and image reconstruction on dense scattering media.",
keywords = "Focusing, Imaging, Inverse scattering, Optimization, Phase modulation, Transmission matrix",
author = "Yujun Chen and Sharma, {Manoj Kumar} and Ashutosh Sabharwal and Ashok Veeraraghavan and Sankaranarayanan, {Aswin C.}",
note = "Publisher Copyright: {\textcopyright} 2020, Springer Nature Switzerland AG.; 16th European Conference on Computer Vision, ECCV 2020 ; Conference date: 23-08-2020 Through 28-08-2020",
year = "2020",
doi = "10.1007/978-3-030-58598-3_19",
language = "English (US)",
isbn = "9783030585976",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "310--326",
editor = "Andrea Vedaldi and Horst Bischof and Thomas Brox and Jan-Michael Frahm",
booktitle = "Computer Vision – ECCV 2020 - 16th European Conference, 2020, Proceedings",
address = "Germany",
}