2008
DOI: 10.1007/978-3-540-79353-3_1
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Optical Configurations for Imaging Spectrometers

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Cited by 3 publications
(10 citation statements)
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“…In comparison, to achieve spectral selectivity, many systems rely on spectral filters, such as spectral filter arrays (SFA), ,,,− where each pixel records only one spectral component of its input light, which leads to a loss in efficiency. An SFA approach where four separate pixels collect three different spectral components, must have efficiencies less than 25% for at least two spectral components. ,, Moreover, in a snapshot system composed of spectral filters, each pixel gets its input light from a separate part of a scene, which necessitates the implementation of spatial interpolation in postprocessing and leads to artifacts and spatial coregistration errors between different spectral channels. ,,,,,, Our device, on the other hand, achieves simultaneous decomposition of incident light into multiple spectral components on the same subwavelength-size pixel area, which drastically reduces spatial coregistration errors and eliminates the need of spatial interpolation. We should also note that our device works better in the spectral ranges where metals have less loss.…”
Section: Resultsmentioning
confidence: 99%
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“…In comparison, to achieve spectral selectivity, many systems rely on spectral filters, such as spectral filter arrays (SFA), ,,,− where each pixel records only one spectral component of its input light, which leads to a loss in efficiency. An SFA approach where four separate pixels collect three different spectral components, must have efficiencies less than 25% for at least two spectral components. ,, Moreover, in a snapshot system composed of spectral filters, each pixel gets its input light from a separate part of a scene, which necessitates the implementation of spatial interpolation in postprocessing and leads to artifacts and spatial coregistration errors between different spectral channels. ,,,,,, Our device, on the other hand, achieves simultaneous decomposition of incident light into multiple spectral components on the same subwavelength-size pixel area, which drastically reduces spatial coregistration errors and eliminates the need of spatial interpolation. We should also note that our device works better in the spectral ranges where metals have less loss.…”
Section: Resultsmentioning
confidence: 99%
“…In many areas of science and technology that utilize the spectrum of light, such as spectroscopy, multispectral imaging, hyperspectral imaging, and wavelength demultiplexing, it is desired to decompose light into its spectral components with minimum photon loss. Especially, in snapshot imaging applications, where the goal is to simultaneously collect full spatial and spectral information, one needs to perform the spectral decomposition in a photon-efficient manner, without sacrificing spatial resolution, which is conventionally limited by diffraction. ,, Furthermore, imaging systems are increasingly miniaturized, and pixels in image sensors or focal plane arrays tend to shrink down to the (sub)­wavelength scale, which are driven in part by the small form factor requirement on mobile platforms. , Hence, there is an urgent need for a photon-efficient, compact, subwavelength-size spectral light separator to build high-resolution, low-cost, low-power, and lightweight multispectral snapshot imaging systems. ,, …”
mentioning
confidence: 99%
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“…Existen diferentes técnicas para la adquisición de imágenes hiperespectrales con diferentes métodos de adquisición de una imagen del cubo de datos (whiskbroom, pushbroom, framing o windowing) y con diferentes procedimientos de obtención de la información espectral (elementos dispersivos, sistemas basados en filtros o espectrómetros por transformada de Fourier) [10]. Este trabajo se ha centrado en el desarrollo de espectrómetros de imagen dispersivos tipo pushbroom.…”
Section: A Espectrómetros De Imagen Dispersivos Tipo Pushbroom: Siunclassified