Longwave infrared multispectral image sensor system using
aluminum-germanium plasmonic filter arrays
- URL: http://arxiv.org/abs/2303.01661v1
- Date: Fri, 3 Mar 2023 01:47:32 GMT
- Title: Longwave infrared multispectral image sensor system using
aluminum-germanium plasmonic filter arrays
- Authors: Noor E Karishma Shaik, Bryce Widdicombe, Dechuan Sun, Sam E John,
Dongryeol Ryu, Ampalavanapillai Nirmalathas, Ranjith R Unnithan
- Abstract summary: A multispectral camera records image data in various wavelengths across the electromagnetic spectrum to acquire additional information that a conventional camera fails to capture.
We experimentally demonstrate an LWIR multispectral image sensor with three wavelength bands using optical elements made of an aluminum-based plasmonic filter array sandwiched in germanium.
Our work demonstrates a versatile spectral thermography technique for detecting target signatures in the LWIR range and other advanced spectral analyses.
- Score: 0.8081564951955755
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: A multispectral camera records image data in various wavelengths across the
electromagnetic spectrum to acquire additional information that a conventional
camera fails to capture. With the advent of high-resolution image sensors and
colour filter technologies, multispectral imagers in the visible wavelengths
have become popular with increasing commercial viability in the last decade.
However, multispectral imaging in longwave infrared (LWIR: 8 to 14 microns) is
still an emerging area due to the limited availability of optical materials,
filter technologies, and high-resolution sensors. Images from LWIR
multispectral cameras can capture emission spectra of objects to extract
additional information that a human eye fails to capture and thus have
important applications in precision agriculture, forestry, medicine, and object
identification. In this work, we experimentally demonstrate an LWIR
multispectral image sensor with three wavelength bands using optical elements
made of an aluminum-based plasmonic filter array sandwiched in germanium. To
realize the multispectral sensor, the filter arrays are then integrated into a
3D printed wheel stacked on a low-resolution monochrome thermal sensor. Our
prototype device is calibrated using a blackbody and its thermal output has
been enhanced with computer vision methods. By applying a state-of-the-art deep
learning method, we have also reconstructed multispectral images to a better
spatial resolution. Scientifically, our work demonstrates a versatile spectral
thermography technique for detecting target signatures in the LWIR range and
other advanced spectral analyses.
Related papers
- Multispectral Stereo-Image Fusion for 3D Hyperspectral Scene
Reconstruction [4.2056926734482065]
We present a novel approach combining two calibrated multispectral real-time capable snapshot cameras, covering different spectral ranges, into a stereo-system.
The combined use of different multispectral snapshot cameras enables both 3D reconstruction and spectral analysis.
arXiv Detail & Related papers (2023-12-15T13:20:35Z) - Spec-NeRF: Multi-spectral Neural Radiance Fields [9.242830798112855]
We propose Multi-spectral Neural Radiance Fields(Spec-NeRF) for jointly reconstructing a multispectral radiance field and spectral sensitivity functions(SSFs) of the camera from a set of color images filtered by different filters.
Our experiments on both synthetic and real scenario datasets demonstrate that utilizing filtered RGB images with learnable NeRF and SSFs can achieve high fidelity and promising spectral reconstruction.
arXiv Detail & Related papers (2023-09-14T16:17:55Z) - High Spectral Spatial Resolution Synthetic HyperSpectral Dataset form
multi-source fusion [7.249349307341409]
This research paper introduces a synthetic hyperspectral dataset that combines high spectral and spatial resolution imaging.
The proposed dataset addresses this limitation by leveraging three modalities: RGB, push-broom visible hyperspectral camera, and snapshot infrared hyperspectral camera.
arXiv Detail & Related papers (2023-06-25T11:17:12Z) - Snapshot Multispectral Imaging Using a Diffractive Optical Network [2.8880000014100506]
We present a diffractive optical network-based multispectral imaging system trained using deep learning.
This diffractive multispectral imager performs spatially-coherent imaging over a large spectrum.
We experimentally demonstrate a diffractive multispectral imager based on a 3D-printed diffractive network.
arXiv Detail & Related papers (2022-12-10T05:54:24Z) - Decoupled-and-Coupled Networks: Self-Supervised Hyperspectral Image
Super-Resolution with Subpixel Fusion [67.35540259040806]
We propose a subpixel-level HS super-resolution framework by devising a novel decoupled-and-coupled network, called DCNet.
As the name suggests, DC-Net first decouples the input into common (or cross-sensor) and sensor-specific components.
We append a self-supervised learning module behind the CSU net by guaranteeing the material consistency to enhance the detailed appearances of the restored HS product.
arXiv Detail & Related papers (2022-05-07T23:40:36Z) - Tuning IR-cut Filter for Illumination-aware Spectral Reconstruction from
RGB [84.1657998542458]
It has been proven that the reconstruction accuracy relies heavily on the spectral response of the RGB camera in use.
This paper explores the filter-array based color imaging mechanism of existing RGB cameras, and proposes to design the IR-cut filter properly for improved spectral recovery.
arXiv Detail & Related papers (2021-03-26T19:42:21Z) - Data-Driven Discovery of Molecular Photoswitches with Multioutput
Gaussian Processes [51.17758371472664]
Photoswitchable molecules display two or more isomeric forms that may be accessed using light.
We present a data-driven discovery pipeline for molecular photoswitches underpinned by dataset curation and multitask learning.
We validate our proposed approach experimentally by screening a library of commercially available photoswitchable molecules.
arXiv Detail & Related papers (2020-06-28T20:59:03Z) - Exploring Thermal Images for Object Detection in Underexposure Regions
for Autonomous Driving [67.69430435482127]
Underexposure regions are vital to construct a complete perception of the surroundings for safe autonomous driving.
The availability of thermal cameras has provided an essential alternate to explore regions where other optical sensors lack in capturing interpretable signals.
This work proposes a domain adaptation framework which employs a style transfer technique for transfer learning from visible spectrum images to thermal images.
arXiv Detail & Related papers (2020-06-01T09:59:09Z) - Quantum metamaterial for nondestructive microwave photon counting [52.77024349608834]
We introduce a single-photon detector design operating in the microwave domain based on a weakly nonlinear metamaterial.
We show that the single-photon detection fidelity increases with the length of the metamaterial to approach one at experimentally realistic lengths.
In stark contrast to conventional photon detectors operating in the optical domain, the photon is not destroyed by the detection and the photon wavepacket is minimally disturbed.
arXiv Detail & Related papers (2020-05-13T18:00:03Z) - Hyperspectral-Multispectral Image Fusion with Weighted LASSO [68.04032419397677]
We propose an approach for fusing hyperspectral and multispectral images to provide high-quality hyperspectral output.
We demonstrate that the proposed sparse fusion and reconstruction provides quantitatively superior results when compared to existing methods on publicly available images.
arXiv Detail & Related papers (2020-03-15T23:07:56Z) - Hyperspectral Infrared Microscopy With Visible Light [0.4893345190925178]
We introduce a new approach to IR hyperspectral microscopy, where the IR spectral map of the sample is obtained with off-the-shelf components built for visible light.
The technique provides a wide field of view, fast readout, and negligible heat delivered to the sample, which makes it highly relevant to material and biological applications.
arXiv Detail & Related papers (2020-02-14T10:29:32Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.