Compressed sensing snapshot spectral imaging by a regular digital camera with an added optical diffuser

Golub, Michael A.; Averbuch, Amir; Nathan, M.; Zheludev, Valery A.; Hauser, Jonathan; Gurevitch, Shay; Malinsky, Roman; Kagan, Asaf

doi:10.1364/ao.55.000432

Cited by 51 publications

(16 citation statements)

References 45 publications

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“…In one of the applications, whose results are to be published soon, directional qWPs are used with Compressed Sensing methodology for the conversion of a regular digital photo camera to an hyperspectral imager. Preliminary results appear in [9]. Special efforts are on the way for the design of a denoising scheme which fully explores the directionality properties of qWPs.…”

Section: Discussionmentioning

confidence: 99%

Analytic and directional wavelet packets

Averbuch

Neittaanmäki²,

Zheludev

2019

2019 13th International Conference on Sampling Theory and Applications (SampTA)

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The paper presents a versatile library of analytic and quasi-analytic complex-valued wavelet packets (WPs) which originate from discrete splines of arbitrary orders. The real parts of the quasi-analytic WPs are the regular spline-based orthonormal WPs designed in [2]. The imaginary parts are the so-called complementary orthonormal WPs, which, unlike the symmetric regular WPs, they are antisymmetric. Tensor products of 1D quasi-analytic WPs provide a diversity of 2D WPs oriented in multiple directions. For example, a set of the fourth-level WPs comprises 62 different directions. The designed computational scheme in the paper enables us to get fast and easy implementation of the WP transforms. The presented WPs proved to be efficient in signal/image processing applications such as restoration of images degraded by either additive noise or missing of up to 90% of their pixels.

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Section: Discussionmentioning

confidence: 99%

Analytic and directional wavelet packets

Averbuch

Neittaanmäki²,

Zheludev

2019

2019 13th International Conference on Sampling Theory and Applications (SampTA)

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“…Another snapshot-based HS imaging method is based on combining a digital camera with an optical diffuser [18], more specifically a restricted isometry property (RIP) diffuser. The RIP diffuser diffuses the light onto the sensor, and a custom algorithm, relying on the RIP condition of the diffuser and sparsity of the reconstruction solution in some wavelet-frame domain, performs the reconstruction of the hyperspectral cube using a linear interactive split Bregman method [23].…”

Section: Passive Hyperspectral Imagingmentioning

confidence: 99%

“…To combine low cost with fast image acquisition, we need snapshot imaging without active mechanical elements. This can be done by using a diffraction grating filter [14][15][16], a prism [17], or an optical diffuser [18], followed by algorithmic reconstruction of the HS image. The existing work in this direction, however, has serious limitations.…”

Section: Introductionmentioning

confidence: 99%

Snapshot hyperspectral imaging using wide dilation networks

Toivonen

Rajani

Klami

2020

Machine Vision and Applications

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Hyperspectral (HS) cameras record the spectrum at multiple wavelengths for each pixel in an image, and are used, e.g., for quality control and agricultural remote sensing. We introduce a fast, cost-efficient and mobile method of taking HS images using a regular digital camera equipped with a passive diffraction grating filter, using machine learning for constructing the HS image. The grating distorts the image by effectively mapping the spectral information into spatial dislocations, which we convert into a HS image by a convolutional neural network utilizing novel wide dilation convolutions that accurately model optical properties of diffraction. We demonstrate high-quality HS reconstruction using a model trained on only 271 pairs of diffraction grating and ground truth HS images.

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“…The diffuser (Golub et al, 2016) for the diffuser's phase function was a randomly permutated, nonlinear saw-tooth phase. Figure 2 illustrates a portion of the diffuser's phase profile.…”

Section: * Corresponding Authormentioning

confidence: 99%

Snapshot Spectral and Color Imaging Using a Regular Digital Camera With a Monochromatic Image Sensor

Hauser

Zheludev

Golub

et al. 2017

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Commission III, WG III/4KEY WORDS: Multispectral and hyperspectral imaging, Imaging systems, Computational Imaging. ABSTRACT:"Spectral imaging" (SI) refers to the acquisition of the three-dimensional (3D) spectral cube of spatial and spectral data of a source object at a limited number of wavelengths in a given wavelength range. "Snapshot spectral imaging" (SSI) refers to the instantaneous acquisition (in a single "shot") of the spectral cube, a process suitable for fast changing objects. Known SSI devices exhibit large total track length (TTL), weight and production costs and relatively low optical throughput. We present a simple SSI camera based on a regular digital camera with (i) an added diffusing and dispersing "phase-only" static optical element at the entrance pupil ("diffuser") and (ii) tailored compressed sensing (CS) methods for digital processing of the diffused and dispersed (DD) image recorded on the image sensor. The diffuser is designed to mix the spectral cube data spectrally and spatially and thus to enable convergence in its reconstruction by CS-based algorithms. In addition to performing SSI, this SSI camera is capable to perform color imaging using a "monochromatic" or "gray-scale" image sensor without color filter arrays.

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Compressed sensing snapshot spectral imaging by a regular digital camera with an added optical diffuser

Abstract: We propose a spectral imaging method that allows a regular digital camera to be converted into a snapshot spectral imager by equipping the camera with a dispersive diffuser and with a compressed sensing-based algorithm for digital processing. Results of optical experiments are reported.

Cited by 51 publications

References 45 publications

Analytic and directional wavelet packets

Analytic and directional wavelet packets

Snapshot hyperspectral imaging using wide dilation networks

Snapshot Spectral and Color Imaging Using a Regular Digital Camera With a Monochromatic Image Sensor

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