Snapshot depth–spectral imaging based on image mapping and light field

EURASIP Journal on Advances in Signal Processing

Research

Liang Hu¹  Shubo Zhou²  Yupeng Li³  Xiaoming Ding³  Tingting Han³  Dunqiang Lu³  Guowei Che³  Xiaocheng Wang³ 

[1] CAS Key Laboratory of Computational Optics Imaging Technology, Aerospace - Information Research Institution, 100094, Beijing, China;Institute of Information Science and Technology, Donghua University, 201620, Shanghai, China;Tianjin Key Laboratory of Wireless Mobile Communications and Power Transmission, Tianjin Normal University, 300387, Tianjin, China;

关键词: Depth estimation;    Light field;    Image mapper;    Spectral imaging;   

DOI  :  10.1186/s13634-023-00983-7

 received in 2022-11-20, accepted in 2023-01-23,  发布年份 2023

来源: Springer

【 摘 要 】

Depth–spectral imaging (DSI) is an emerging technology which can obtain and reconstruct the spatial, spectral and depth information of a scene simultaneously. Conventionally, DSI system usually relies on scanning process, multi-sensors or compressed sensing framework to modulate and acquire the entire information. This paper proposes a novel snapshot DSI architecture based on image mapping and light field framework by using a single format detector. Specifically, we acquire the depth – spectral information in two steps. Firstly, an image mapper is utilized to slice and reflect the first image to different directions which is a spatial modulation processing. The modulated light wave is then dispersed by a direct vision prism. After re-collection, the sliced dispersed light wave is recorded by a light field sensor. Complimentary, we also propose a reconstruction strategy to recover the spatial depth – spectral hypercube effectively. We establish a mathematical model to describe the light wave distribution on every optical facet. Through simulations, we generate the aliasing raw spectral light field data. Under the reconstruction strategy, we design an algorithm to recover the hypercube accurately. Also, we make an analysis about the spatial and spectral resolution of the reconstructed data, the evaluation results conform the expectation.

【 授权许可】

CC BY   
© The Author(s) 2023

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