Spatial-spectral modulating snapshot hyperspectral imager

Johnson, William R.; Wilson, Daniel W.; Bearman, Greg

doi:10.1364/ao.45.001898

Cited by 33 publications

(19 citation statements)

References 12 publications

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“…Image replication imaging spectrometer (IRIS) [Gorman et al 2010] uses a series of polarization beamsplitters and performs spectral selection based on the principle of generalized Lyot filter. Computed tomography imaging spectrometer (CTIS) [Johnson et al 2006] captures multiple projections of the 3D data cube onto the sensor with the computer-generated hologram disperser, with which the spectral images can be tomographically reconstructed. Prism-mask multispectral video imaging system (PMVIS) [Du et al 2009] simply employs an occlusion mask and a prism which allows for different trade-offs between spectral and spatial resolution.…”

Section: Related Workmentioning

confidence: 99%

Spatial-spectral encoded compressive hyperspectral imaging

et al. 2014

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Figure 1: 3D hyperspectral (HS) images reconstructed from a single spatial-spectral encoded 2D projection for an outdoor scene under sunlight environment. Left-most: The sensor image captured by our camera prototype. Second-by-left: Recovered high-spatial resolution 3D HS images with color indicating 31 spectral bands from 420nm to 720nm. Third and fourth: Closeup of recovered 520nm and 650nm spectral bands images. Right-most: The synthetic RGB image from the reconstructed HS images. AbstractThis paper proposes a novel compressive hyperspectral (HS) imaging approach that allows for high-resolution HS images to be captured in a single image. The proposed architecture comprises three key components: spatial-spectral encoded optical camera design, over-complete HS dictionary learning and sparse-constraint computational reconstruction. Our spatial-spectral encoded sampling scheme provides a higher degree of randomness in the measured projections than previous compressive HS imaging approaches; and a robust nonlinear sparse reconstruction method is employed to recover the HS images from the coded projection with higher performance. To exploit the sparsity constraint on the nature HS images for computational reconstruction, an over-complete HS dictionary is learned to represent the HS images in a sparser way than previous representations. We validate the proposed approach on both synthetic and real captured data, and show successful recovery of HS images for both indoor and outdoor scenes. In addition, we demonstrate other applications for the over-complete HS dictionary and sparse coding techniques, including 3D HS images compression and denoising.

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Section: Related Workmentioning

confidence: 99%

Spatial-spectral encoded compressive hyperspectral imaging

et al. 2014

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“…Spatially or spectrally scanning affords the best resolution at the cost of motion artifact as the data is acquired over time. Recent work has been focused at improving "snapshot" technologies to make use of the lack of motion artifact [84]. By combining multiple wavelengths, HRI has the potential to identify spectral coefficients for macular pigments, drusen subtypes, and (deoxy-) hemoglobin [85][86][87].…”

Section: Hyperspectral Retinal Imaging (Hri)mentioning

confidence: 99%

Drusen Imaging: A Review

Hunter¹

2014

J Clin Exp Ophthalmol

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Drusen represent the hallmark of non-exudative age-related macular degeneration (AMD). Drusen vary in their location within the retina, ranging from sub-retinal pigment epithelium (RPE) drusen and sub-neurosensory retinal drusenoid deposits above the RPE (or pseudo-drusen). In this paper, we review the rapidly advancing imaging techniques currently available to better correlate drusen volume to clinical stage. This includes, but is not limited to, fundus photography, fluorescein angiography, optical coherence tomography, infrared imaging, fundus autofluorescence, confocal adaptive-optics imaging, and hyperspectral retinal imaging. A new understanding of drusen role in the pathogenesis of the disease may be possible with these imaging modalities in future clinical studies.

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“…Moreover, its main limitation as a snapshot instrument is due to the nature of its ill-posed process of acquisition of limited angle projection tomography. Spectral reconstruction accuracy and resolution are thus highly scene dependent and further depend on the iterative algorithm and iteration stopping criteria [10] [11]. Coded aperture snapshot spectral imagers (CASSI) [12][13] attempt to overcome the limits of the spatial versus spectral resolution multiplexing trade-off by undersampling the scene spatially in each band and using compressive sensing to reconstruct the full spatial resolution.…”

Section: State Of the Artmentioning

confidence: 99%

A snapshot multispectral imager with integrated tiled filters and optical duplication

2013

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Although the potential of spectral imaging has been demonstrated in research environments, its adoption by industry has so far been limited due to the lack of high speed, low cost and compact spectral cameras. We have previously presented work to overcome this limitation by monolithically integrating optical interference filters on top of standard CMOS image sensors for high resolution pushbroom hyperspectral cameras. These cameras require a scanning of the scene and therefore introduce operator complexity due to the need for synchronization and alignment of the scanning to the camera. This typically leads to problems with motion blur, reduced SNR in high speed applications and detection latency and overall restricts the types of applications that can use this system. This paper introduces a novel snapshot multispectral imager concept based on optical filters monolithically integrated on top of a standard CMOS image sensor. By using monolithic integration for the dedicated, high quality spectral filters at its core, it enables the use of mass-produced fore-optics, reducing the total system cost. It overcomes the problems mentioned for scanning applications by snapshot acquisition, where an entire multispectral data cube is sensed at one discrete point in time. This is achieved by applying a novel, tiled filter layout and an optical sub-system which simultaneously duplicates the scene onto each filter tile. Through the use of monolithically integrated optical filters it retains the qualities of compactness, low cost and high acquisition speed, differentiating it from other snapshot spectral cameras based on heterogeneously integrated custom optics. Moreover, thanks to a simple cube assembly process, it enables real-time, low-latency operation. Our prototype camera can acquire multispectral image cubes of 256x256 pixels over 32 bands in the spectral range of 600-1000nm at a speed of about 30 cubes per second at daylight conditions up to 340 cubes per second at higher illumination levels as typically used in machine vision applications.

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Spatial-spectral modulating snapshot hyperspectral imager

Cited by 33 publications

References 12 publications

Spatial-spectral encoded compressive hyperspectral imaging

Spatial-spectral encoded compressive hyperspectral imaging

Drusen Imaging: A Review

A snapshot multispectral imager with integrated tiled filters and optical duplication

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