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Register a new userHybrid colour filters for multispectral imaging
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Added by
Ranjith Unnithan Dr
Publication date
2020
fields
Physics
and research's language is
English
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Multispectral cameras capture images in multiple wavelengths in narrow spectral bands. They offer advanced sensing well beyond normal cameras and many single sensor based multispectral cameras have been commercialized aimed at a broad range of applications, such as agroforestry research, medical analysis and so on. However, the existing single sensor based multispectral cameras require accurate alignment to overlay each filter on image sensor pixels, which makes their fabrication very complex, especially when the number of bands is large. This paper demonstrates a new filter technology using a hybrid combination of single plasmonic layer and dielectric layers by computational simulations. A filter mosaic of various bands with narrow spectral width can be achieved with single run manufacturing processes (i.e., exposure, development, deposition and other minor steps), regardless of the number of bands.
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Multispectral imaging plays an important role in many applications from astronomical imaging, earth observation to biomedical imaging. However, the current technologies are complex with multiple alignment-sensitive components, predetermined spatial and spectral parameters by manufactures. Here, we demonstrate a single-shot multispectral imaging technique that gives flexibility to end-users with a very simple optical setup, thank to spatial correlation and spectral decorrelation of speckle patterns. These seemingly random speckle patterns are point spreading functions (PSFs) generated by light from point sources propagating through a strongly scattering medium. The spatial correlation of PSFs allows image recovery with deconvolution techniques, while the spectral decorrelation allows them to play the role of tune-able spectral filters in the deconvolution process. Our demonstrations utilizing optical physics of strongly scattering media and computational imaging present the most cost-effective approach for multispectral imaging with great advantages.
A multispectral image camera captures image data within specific wavelength ranges in narrow wavelength bands across the electromagnetic spectrum. Images from a multispectral camera can extract additional information that the human eye or a normal camera fails to capture and thus may have important applications in precision agriculture, forestry, medicine and object identification. Conventional multispectral cameras are made up of multiple image sensors each fitted with a narrow passband wavelength filter and optics, which makes them heavy, bulky, power hungry and very expensive. The multiple optics also create image co-registration problem. Here, we demonstrate a single sensor based three band multispectral camera using a narrow spectral band RGB colour mosaic in a Bayer pattern integrated on a monochrome CMOS sensor. The narrow band colour mosaic is made of a hybrid combination of plasmonic colour filters and heterostructured dielectric multilayer. The demonstrated camera technology has reduced cost, weight, size and power by almost n times (where n is the number of bands) compared to a conventional multispectral camera.
Fluorescence microscopy is a powerful tool to measure molecular specific information in biological samples. However, most biological tissues are highly heterogeneous because of refractive index (RI) differences and thus degrade the signal-to-noise ratio of fluorescence images. At the same time, RI is an intrinsic optical property of label free biological tissues that quantitatively relates to cell morphology, mass, and stiffness. Conventional imaging techniques measure fluorescence and RI of biological samples separately. Here, we develop a new computational hybrid imaging method based on a multi-slice model of multiple scattering that reconstructs 3D fluorescence and 3D RI from the same dataset of fluorescence images. Our method not only bridges the gap between fluorescence and RI imaging and provides a panoramic view of the biological samples, but also can digitally correct multiple scattering effect of fluorescence images from the reconstructed 3D RI. Computational hybrid imaging opens a unique avenue beyond conventional imaging techniques.
Multispectral imaging systems (MISs) have been used widely to analyze adulteration and toxin formation in oil, yet a dearth of attention has been tendered to oil reheating and reusing despite the consumption of such debased oil being deleterious. To that end, the paper discusses the application of MISs to estimate the reheat cycle count classes (number of times an oil sample is recursively heated) and to identify critical classes at which substantial changes in the oil sample have materialized. The MIS captures the transmittance spectrum of the translucent specimen as opposed to other multispectral imaging research which often measures the reflected light from opaque solid samples. Firstly, the reheat cycle count class is estimated with Bhattacharyya distance between the reheated and a pure oil sample as the input. The classification was performed using a support vector machine classifier that resulted in an accuracy of 83.34 % for reheat cycle count identification. Subsequently, to distinguish critical classes under reheating, an unsupervised clustering procedure was introduced using a modified spectral clustering (SC) algorithm. In addition, laboratory experiments were performed to ascertain the ramifications of the reheating process with a chemical analysis. The chemical analysis of the coconut oil samples used in the experiment yielded that a statistically significant change (p < 0.05) had taken place in the chemical properties with reheating and the results of the proposed SC framework were deemed to coincide with the chemical analysis results.
We report on the integration of large area CVD grown single- and bilayer graphene transparent conductive electrodes (TCEs) on amorphous silicon multispectral photodetectors. The broadband transmission of graphene results in 440% enhancement of the detectors spectral response in the ultraviolet (UV) region at {lambda} = 320 nm compared to reference devices with conventional aluminum doped zinc oxide (ZnO:Al) electrodes. The maximum responsivity of the multispectral photodetectors can be tuned in their wavelength from 320 nm to 510 nm by an external bias voltage, allowing single pixel detection of UV to visible light. Graphene electrodes further enable fully flexible diodes on polyimide substrates. Here, an upgrade from single to bilayer graphene boosts the maximum photoresponsivity from 134 mA $W^{-1}$ to 239 mA $W^{-1}$. Interference patterns that are present in conventional TCE devices are suppressed as a result of the atomically thin graphene electrodes. The proposed detectors may be of interest in fields of UV/VIS spectroscopy or for biomedical and life science applications, where the extension to the UV range can be essential.
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