Sequential Transmission Matrix Evaluation Via Spatiotemporal Transmitted Modes Decomposition

TL;DR

This paper introduces a novel method for decomposing and sequentially evaluating the transmission matrix in scattering media, enabling high-dimensional control and improved image reconstruction.

Contribution

It proposes a decomposition approach that leverages spatiotemporal invariance to efficiently evaluate large transmission matrices with enhanced control and noise optimization.

Findings

Achieves high-dimensional transmission matrix evaluation

Improves signal-to-noise ratio during evaluation

Enhances image focusing and reconstruction capabilities

Abstract

The transmission matrix (TM) is a representation to describe the light scattering process through a scattering medium. The degree of control elements in TM is correlated with the capacity of evaluating enormous equations with tremendous number of unknow parameters, which seriously restricts the efficiency and accuracy of TM, and thus further confines applications such as image recovery. To completely remove this restriction, we propose decomposing TM and sequentially acquiring the dimension reduced decompositions regarding to the time and space invariance nature of transmitted field behind scattering medium. This proposed approach would not only have the ability to achieve high dimension transmission matrix with fully controllable elements, but also brings optimized signal-to-noise ratio during evaluation processing, which provides researchers a way to reach maximal focusing efficiency or image reconstruction resolution.