Computational imaging of moving objects obscured by a random corridor via speckle correlations

Tian Shi, Liangsheng Li*, He Cai, Xianli Zhu, Qingfan Shi, Ning Zheng*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

11 Citations (Scopus)

Abstract

Computational imaging makes it possible to reconstruct hidden objects through random media and around corners, which is of fundamental importance in various fields. Despite recent advances, computational imaging has not been studied in certain types of random scenarios, such as tortuous corridors filled with random media. We refer to this category of complex environment as a ’random corridor’, and propose a reduced spatial- and ensemble-speckle intensity correlation (RSESIC) method to image a moving object obscured by a random corridor. Experimental results show that the method can reconstruct the image of a centimeter-sized hidden object with a sub-millimeter resolution by a low-cost digital camera. The imaging capability depends on three system parameters and can be characterized by the correlation fidelity (CF). Furthermore, the RSESIC method is able to recover the image of objects even for a single pixel containing the contribution of about 102 speckle grains, which overcomes the theoretical limitation of traditional speckle imaging methods. Last but not least, when the power attenuation of speckle intensity leads to serious deterioration of CF, the image of hidden objects can still be reconstructed by the corrected intensity correlation.

Original languageEnglish
Article number4081
JournalNature Communications
Volume13
Issue number1
DOIs
Publication statusPublished - Dec 2022

Fingerprint

Dive into the research topics of 'Computational imaging of moving objects obscured by a random corridor via speckle correlations'. Together they form a unique fingerprint.

Cite this