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Main Authors: Bian, Liheng, Wang, Zhen, Zhang, Yuzhe, Li, Lianjie, Zhang, Yinuo, Yang, Chen, Fang, Wen, Zhao, Jiajun, Zhu, Chunli, Meng, Qinghao, Peng, Xuan, Zhang, Jun
Format: Preprint
Published: 2023
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Online Access:https://arxiv.org/abs/2306.11583
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author Bian, Liheng
Wang, Zhen
Zhang, Yuzhe
Li, Lianjie
Zhang, Yinuo
Yang, Chen
Fang, Wen
Zhao, Jiajun
Zhu, Chunli
Meng, Qinghao
Peng, Xuan
Zhang, Jun
author_facet Bian, Liheng
Wang, Zhen
Zhang, Yuzhe
Li, Lianjie
Zhang, Yinuo
Yang, Chen
Fang, Wen
Zhao, Jiajun
Zhu, Chunli
Meng, Qinghao
Peng, Xuan
Zhang, Jun
contents Hyperspectral imaging provides high-dimensional spatial-temporal-spectral information revealing intrinsic matter characteristics. Here we report an on-chip computational hyperspectral imaging framework with high spatial and temporal resolution. By integrating different broadband modulation materials on the image sensor chip, the target spectral information is non-uniformly and intrinsically coupled on each pixel with high light throughput. Using intelligent reconstruction algorithms, multi-channel images can be recovered from each frame, realizing real-time hyperspectral imaging. Following such a framework, we for the first time fabricated a broadband VIS-NIR (400-1700 nm) hyperspectral imaging sensor using photolithography, with an average light throughput of 74.8% and 96 wavelength channels. The demonstrated resolution is 1,024*1,024 pixels at 124 fps. We demonstrated its wide applications including chlorophyll and sugar quantification for intelligent agriculture, blood oxygen and water quality monitoring for human health, textile classification and apple bruise detection for industrial automation, and remote lunar detection for astronomy. The integrated hyperspectral image sensor weighs only tens of grams, and can be assembled on various resource-limited platforms or equipped with off-the-shelf optical systems. The technique transforms the challenge of high-dimensional imaging from a high-cost manufacturing and cumbersome system to one that is solvable through on-chip compression and agile computation.
format Preprint
id arxiv_https___arxiv_org_abs_2306_11583
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle A broadband hyperspectral image sensor with high spatio-temporal resolution
Bian, Liheng
Wang, Zhen
Zhang, Yuzhe
Li, Lianjie
Zhang, Yinuo
Yang, Chen
Fang, Wen
Zhao, Jiajun
Zhu, Chunli
Meng, Qinghao
Peng, Xuan
Zhang, Jun
Optics
Hyperspectral imaging provides high-dimensional spatial-temporal-spectral information revealing intrinsic matter characteristics. Here we report an on-chip computational hyperspectral imaging framework with high spatial and temporal resolution. By integrating different broadband modulation materials on the image sensor chip, the target spectral information is non-uniformly and intrinsically coupled on each pixel with high light throughput. Using intelligent reconstruction algorithms, multi-channel images can be recovered from each frame, realizing real-time hyperspectral imaging. Following such a framework, we for the first time fabricated a broadband VIS-NIR (400-1700 nm) hyperspectral imaging sensor using photolithography, with an average light throughput of 74.8% and 96 wavelength channels. The demonstrated resolution is 1,024*1,024 pixels at 124 fps. We demonstrated its wide applications including chlorophyll and sugar quantification for intelligent agriculture, blood oxygen and water quality monitoring for human health, textile classification and apple bruise detection for industrial automation, and remote lunar detection for astronomy. The integrated hyperspectral image sensor weighs only tens of grams, and can be assembled on various resource-limited platforms or equipped with off-the-shelf optical systems. The technique transforms the challenge of high-dimensional imaging from a high-cost manufacturing and cumbersome system to one that is solvable through on-chip compression and agile computation.
title A broadband hyperspectral image sensor with high spatio-temporal resolution
topic Optics
url https://arxiv.org/abs/2306.11583