High-resolution hyperspectral single-pixel imaging system based on compressive sensing

Magalhães, Filipe; Araújo, F. M.; Correia, Miguel Velhote; Abolbashari, Mehrdad; Farahi, Faramarz

doi:10.1117/1.oe.51.7.071406

Cited by 56 publications

(20 citation statements)

References 15 publications

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“…We thus can control the total number of coefficients n acquired for each decomposition level by modulating the set of percentages P in (12). Using (13), it can be shown that…”

Section: Compression Ratementioning

confidence: 99%

Adaptive Basis Scan by Wavelet Prediction for Single-Pixel Imaging

Rousset

Ducros

Farina³

et al. 2017

IEEE Trans. Comput. Imaging

114

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Single pixel camera imaging is an emerging paradigm that allows high-quality images to be provided by a device only equipped with a single point detector. A single pixel camera is an experimental setup able to measure the inner product of the scene under view-the image-with any user-defined pattern. Post-processing a sequence of point measurements obtained with different patterns permits to recover spatial information, as it has been demonstrated by state-of-theart approaches belonging to the compressed sensing framework. In this paper, a new framework for the choice of the patterns is proposed together with a simple and efficient image recovery scheme. Our goal is to overcome the computationally demanding 1-minimization of compressed sensing. We propose to choose patterns among a wavelet basis in an adaptive fashion, which essentially relies onto the prediction of the significant wavelet coefficients' location. More precisely, we adopt a multiresolution strategy that exploits the set of measurements acquired at coarse scales to predict the set of measurements to be performed at a finer scale. Prediction is based on a fast cubic interpolation in the image domain. A general formalism is given so that any kind of wavelets can be used, which enables one to adjust the wavelet to the type of images related to the desired application. Both simulated and experimental results demonstrate the ability of our technique to reconstruct biomedical images with improved quality compared to CS-based recovery. Application to real-time fluorescence imaging of biological tissues could benefit from the proposed method.

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“…We thus can control the total number of coefficients n acquired for each decomposition level by modulating the set of percentages P in (12). Using (13), it can be shown that…”

Section: Compression Ratementioning

confidence: 99%

Adaptive Basis Scan by Wavelet Prediction for Single-Pixel Imaging

Rousset

Ducros

Farina³

et al. 2017

IEEE Trans. Comput. Imaging

114

View full text Add to dashboard Cite

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“…Different techniques have been proposed, depending on the applications [6], but hyperspectral imaging suffers from trade-offs between the spatial resolution, spectral resolution, light collection, and acquisition rate. Some designs enable the constraint of several of these parameters simultaneously, [7] among them, compressive sensing seems to be a promising method [8].…”

Section: Introductionmentioning

confidence: 99%

Towards Low-Cost Hyperspectral Single-Pixel Imaging for Plant Phenotyping

Ribes

Russias

Trégoat

et al. 2020

Sensors

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Hyperspectral imaging techniques have been expanding considerably in recent years. The cost of current solutions is decreasing, but these high-end technologies are not yet available for moderate to low-cost outdoor and indoor applications. We have used some of the latest compressive sensing methods with a single-pixel imaging setup. Projected patterns were generated on Fourier basis, which is well-known for its properties and reduction of acquisition and calculation times. A low-cost, moderate-flow prototype was developed and studied in the laboratory, which has made it possible to obtain metrologically validated reflectance measurements using a minimal computational workload. From these measurements, it was possible to discriminate plant species from the rest of a scene and to identify biologically contrasted areas within a leaf. This prototype gives access to easy-to-use phenotyping and teaching tools at very low-cost.

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“…One is to resolve the spectra of collected lights at the detector. Existing such methods include i) directly replacing the bucket detector with a spectrometer 21 22 , and ii) using light filters 23 24 or dispersive optical devices 10 25 to separate lights of different wavelengths before separately measuring them. Another straightforward way is to directly extend the 2D spatial modulation in conventional SPI to 3D spatial-spectral modulation using two spatial light modulators.…”

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confidence: 99%

Multispectral imaging using a single bucket detector

Bian

Suo

Situ

et al. 2016

Sci Rep

165

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Existing multispectral imagers mostly use available array sensors to separately measure 2D data slices in a 3D spatial-spectral data cube. Thus they suffer from low photon efficiency, limited spectrum range and high cost. To address these issues, we propose to conduct multispectral imaging using a single bucket detector, to take full advantage of its high sensitivity, wide spectrum range, low cost, small size and light weight. Technically, utilizing the detector’s fast response, a scene’s 3D spatial-spectral information is multiplexed into a dense 1D measurement sequence and then demultiplexed computationally under the single pixel imaging scheme. A proof-of-concept setup is built to capture multispectral data of 64 pixels × 64 pixels × 10 wavelength bands ranging from 450 nm to 650 nm, with the acquisition time being 1 minute. The imaging scheme holds great potentials for various low light and airborne applications, and can be easily manufactured as production-volume portable multispectral imagers.

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High-resolution hyperspectral single-pixel imaging system based on compressive sensing

Cited by 56 publications

References 15 publications

Adaptive Basis Scan by Wavelet Prediction for Single-Pixel Imaging

Adaptive Basis Scan by Wavelet Prediction for Single-Pixel Imaging

Towards Low-Cost Hyperspectral Single-Pixel Imaging for Plant Phenotyping

Multispectral imaging using a single bucket detector

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