A novel CMOS-compatible, monolithically integrated line-scan hyperspectral imager covering the VIS-NIR range

Gonzalez, Pilar; Tack, Klaas; Geelen, Bert; Masschelein, Bart; Charle, Wouter; Vereecke, Bart; Lambrechts, Andy

doi:10.1117/12.2230726

Cited by 13 publications

(19 citation statements)

References 8 publications

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“…In Fig. 1(a), a linear variable filter (LVF) is placed in the focal plane, as indicated in the upper part of the figure, enabling recording of hyperspectral imagery [3], [8]. A spectral image is assembled from multiple raw image frames recorded at different positions during the flight.…”

Section: Imaging Conceptmentioning

confidence: 99%

“…Conventional imaging spectrometers such as HySpex Mjolnir [2] record accurate spectra, but have complex optics and limited pixel count relative to their size. Fabry-Pérot spectral imagers can be compact [3], [4], but are subject to photon noise due to narrow bandwidth, and motion artifacts due to non-simultaneous sampling of bands. Multispectral imagers are available with multiple cameras recording one band each, but such systems grow in size when a large band count and/or good light throughput is needed.…”

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confidence: 99%

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Multimodal Multispectral Imaging System for Small UAVs

Haavardsholm

Skauli

Stahl

2020

IEEE Robot. Autom. Lett.

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Multispectral imaging is an attractive sensing modality for small unmanned aerial vehicles (UAVs) in numerous applications. The most compact spectral camera architecture is based on spectral filters in the focal plane. Vehicle movement can be used to scan the scene using multiple bandpass filters arranged perpendicular to the flight direction. With known camera trajectory and scene structure, it is possible to assemble a spectral image in software. In this letter, we demonstrate the feasibility of a novel concept for low-cost wide area multispectral imaging with integrated spectral consistency testing. Six bandpass filters are arranged in a periodically repeating pattern. Since different bands are recorded at different times and in different viewing directions, there is a risk of obtaining spectral artifacts in the image. We exploit the repeated sampling of bands to enable spectral consistency testing, which leads to significantly improved spectral integrity. In addition, an unfiltered region permits conventional 2D video imaging that can be used for image-based navigation and 3D reconstruction. The proposed multimodal imaging system was tested on a UAV in a realistic experiment. The results demonstrate that spectral reconstruction and consistency testing can be performed by image processing alone, based on visual simultaneous localization and mapping (VSLAM).

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Section: Imaging Conceptmentioning

confidence: 99%

mentioning

confidence: 99%

Multimodal Multispectral Imaging System for Small UAVs

Haavardsholm

Skauli

Stahl

2020

IEEE Robot. Autom. Lett.

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“…We use the Imec Snapscan VNIR range camera system, 37 shown in Figure 3: a camera system concept that combines the high spatial resolution and spectral resolution of line scan hyperspectral imaging technology. 34 It can acquire datasets for a static scene as easily as with a snapshot camera. There is no need for any external scanning movement: scanning is handled internally, using a miniaturised scanning stage.…”

Section: Camera Systemsmentioning

confidence: 99%

“…For the latter we compare a pixel-based classifier such as QDC 15 with the CNNs presented in Blanch et al 33 We analyse the impact as well of pre-and post-processing methods such as spatial/spectral binning, bilateral filtering 29,30 and median filtering. 32,34 We also benchmark our work against colour imaging systems restricted to the human-visible spectrum. To our knowledge, this is the first study where the individual and joint impact of all these system aspects (illumination, analysis method, camera spatial-spectral resolution) is investigated for a specific HSI application.…”

Section: Introductionmentioning

confidence: 99%

Hyperspectral system trade-offs for illumination, hardware and analysis methods: a case study of seed mix ingredient discrimination

Notario

López-Molina

Lambrechts

et al. 2020

J. Spectral Imaging

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The discrimination power of a hyperspectral imaging system for image segmentation or object detection is determined by the illumination, the camera spatial–spectral resolution, and both the pre-processing and analysis methods used for image processing. In this study, we methodically reviewed the alternatives for each of those factors for a case study from the food industry to provide guidance in the construction and configuration of hyperspectral imaging systems in the visible near infrared range for food quality inspection. We investigated both halogen- and LED-based illuminations and considered cameras with different spatial–spectral resolution trade-offs. At the level of the data analysis, we evaluated the impact of binning, median filtering and bilateral filtering as pre- or post-processing and compared pixel-based classifiers with convolutional neural networks for a challenging application in the food industry, namely ingredient identification in a flour–seed mix. Starting from a basic configuration and by modifying the combination of system aspects we were able to increase the mean accuracy by at least 25 %. In addition, different trade-offs in performance-complexity were identified for different combinations of system parameters, allowing adaptation to diverse application requirements.

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“…There are numerous applications that benefit from spectral imaging including remote sensing in agriculture [3][4][5][6] to artwork authentication [7][8][9] to food testing [10]. Numerous line and line-scan spectral imagers have been designed and demonstrated using dispersive optics combined with both pixelated line sensors as well as pixelated 2-D image sensors including efforts to achieve high dynamic ranges (HDR) [11][12][13][14][15][16][17][18][19][20][21]. These instruments have so far been limited in linear dynamic ranges restricted by the 1-D line sensor and 2-D image sensor pixel performances that easily saturate and produce non-linear sensing responses such as commonly observed in the visible, Near IR bands using silicon CMOS and CCD sensors and also noted in eye safe > 1400 nm IR bands for FPA IR sensors.…”

Section: Introductionmentioning

confidence: 99%

CAOS spectral imager design and advanced high dynamic range FDMA–TDMA CAOS mode

Mazhar

Riza

2021

Appl. Opt.

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In the first part of the paper, a CAOS line camera is introduced for spectral imaging of one dimensional (1-D) or line targets. The proposed spectral camera uses both a diffraction grating as well as a cylindrical lens optics system to provide line imaging along the line pixels direction of the image axis and Fourier transforming operations in the orthogonal direction to provide line pixels optical spectrum analysis. The imager incorporates the Digital Micromirror Device (DMD)-based Coded Access Optical Sensor (CAOS) structure. The design includes a line-by-line scan option to enable two dimensional (2-D) spectral imaging. For the first time, demonstrated is line style spectral imaging using a 2850 K color temperature white light target illumination source along with visible band color bandpass filters and a moving mechanical pinhole to simulate a line target with individual pixels along 1-D that have unique spectral content. A ~412 nm to ~732 nm input target spectrum is measured using a 38 × 52 CAOS pixels spatial sampling grid providing a test image line of 38 pixels with each pixel providing a designed spectral resolution of ~6.2 nm. The spectral image is generated using the robust Code Division Multiple Access (CDMA) mode of the camera. The second part of the paper demonstrates for the first time the High Dynamic Range (HDR) operation of the Frequency Division Multiple Access (FDMA)-Time Division Multiple Access (TDMA) mode of the CAOS camera. The FDMA-TDMA mode also feature HDR recovery like the Frequency Modulation (FM)-TDMA mode, although at a much faster imaging rate and a higher Signal-to-Noise Ratio (SNR) as more than one CAOS pixel is extracted at a time. Experiments successfully demonstrate 66 dB HDR target recovery using both FDMA-TDMA and FM-TDMA modes, with the FDMA-TDMA mode operating at an encoding speed 8 times faster than the FM-TDMA mode given 8 FM channels are used for the FDMA-TDMA mode. The CAOS spectral imager can be used to image both full spectrum stationary line targets as well as spectrally map 2-D targets using line scanning methods. The demonstrated FDMA-TDMA CAOS mode is suited for improved speed and SNR linear HDR imaging.

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A novel CMOS-compatible, monolithically integrated line-scan hyperspectral imager covering the VIS-NIR range

Cited by 13 publications

References 8 publications

Multimodal Multispectral Imaging System for Small UAVs

Multimodal Multispectral Imaging System for Small UAVs

Hyperspectral system trade-offs for illumination, hardware and analysis methods: a case study of seed mix ingredient discrimination

CAOS spectral imager design and advanced high dynamic range FDMA–TDMA CAOS mode

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