A compact snapshot multispectral imager with a monolithically integrated per-pixel filter mosaic

Geelen, Bert; Tack, Nicolaas; Lambrechts, Andy

doi:10.1117/12.2037607

Cited by 125 publications

(136 citation statements)

References 11 publications

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“…First, sampling all spectral bands only once in the basic pattern provides the most compact MSFAs, which allows us to consider a high number of channels (16) with limited estimation errors (as shown in the experimental section). Second, an MSFA with a square nonredundant pattern allows us to mimic IMEC's snapshot multispectral camera [3], that is-to our knowledge-the sole off-the-shelf MSFA-based system available on the market today.…”

Section: A Multispectral Filter Arraysmentioning

confidence: 99%

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Multispectral Demosaicing Using Intensity in Edge-Sensing and Iterative Difference-Based Methods

Mihoubi¹,

Losson²,

Mathon³

et al. 2016

2016 12th International Conference on Signal-Image Technology &Amp; Internet-Based Systems (SITIS)

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Single-sensor multispectral cameras, that sample spectral channels using a multispectral filter array, have recently emerged. They provide a raw image in which each channel is spectrally sampled pixel-wise according to the filter array pattern. A demosaicing procedure is then needed to estimate a multispectral image with full spectral resolution. The usefulness of intensity-based demosaicing has been shown in a previous work. In this paper, we both propose an intensity-based adaptation of the Binary Tree-based Edge-Sensing method for raw images with no dominant spectral band, and a new iterative method that uses the central wavelength distance between spectral bands.

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Section: A Multispectral Filter Arraysmentioning

confidence: 99%

“…Recently a single-sensor multispectral snapshot technology has emerged [2][3][4]. It uses a multispectral filter array (MSFA) to capture a single raw image.…”

Section: Introductionmentioning

confidence: 99%

Multispectral Demosaicing Using Intensity in Edge-Sensing and Iterative Difference-Based Methods

Mihoubi¹,

Losson²,

Mathon³

et al. 2016

2016 12th International Conference on Signal-Image Technology &Amp; Internet-Based Systems (SITIS)

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“…For the analysis, we will consider the case of a camera based on N = [ 3,5,8,12] bands. We chose a three-band sensor to represent the typical color case, five bands are chosen for multispectral color sensors or colorimeters [44].…”

Section: Single-parameter Optimizationmentioning

confidence: 99%

“…We use a simple Gaussian model to approximate FabryPérot interferometric filters, such as realized by SILIOS [37] and IMEC [8]. This approximation has been extensively done in the literature, in Fig.…”

Section: Filter Considerationsmentioning

confidence: 99%

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Energy balance in Spectral Filter Array camera design

Lapray

Thomas

Gouton

et al. 2017

J. Eur. Opt. Soc.-Rapid Publ.

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Background: Multispectral imaging permits to capture more spectral information on object surface properties than color imaging. This is useful for machine vision applications. Transmittance spectral filter arrays combined with a solid state sensor form an emerging technology used for snapshot acquisition. In spectral filter arrays technology, the sensitivities of the camera have critical consequences, not only on applications, but also in the viability of the system. We discuss how to balance the energy of each channel in single exposure multispectral imaging. Methods: We propose a methodology to design filters that permits to reach an optimal balance of energy. We apply this method on practical illuminations combined with a Gaussian model of transmittance filters. Results and discussion: Our results demonstrate that we can optimize energetically the global camera response with few efforts for several cases of illumination environments, for a given sensor and a number of spectral channels. This methodology can be embedded in an application-oriented optimization framework. Conclusions: This methodology enables achieving a great range of optical design, and it can be embedded in an application-oriented optimization framework.

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