Jean-Baptiste Thomas

Multispectral Filter Arrays: Recent Advances and Practical Implementation

Thanks to some technical progress in interferencefilter design based on different technologies, we can finally successfully implement the concept of multispectral filter array-based sensors. This article provides the relevant state-of-the-art for multispectral imaging systems and presents the characteristics of the elements of our multispectral sensor as a case study. The spectral characteristics are based on two different spatial arrangements that distribute eight different bandpass filters in the visible and near-infrared area of the spectrum. We demonstrate that the system is viable and evaluate its performance through sensor spectral simulation.

Median filtering in multispectral filter array demosaicking

Inspired by the concept of the colour filter array (CFA), the research community has shown much interest in adapting the idea of CFA to the multispectral domain, producing multispectral filter arrays (MSFAs). In addition to newly devised methods of MSFA demosaicking, there exists a wide spectrum of methods developed for CFA. Among others, some vector based operations can be adapted naturally for multispectral purposes. In this paper, we focused on studying two vector based median filtering methods in the context of MSFA demosaicking. One solves demosaicking problems by means of vector median filters, and the other applies median filtering to the demosaicked image in spherical space as a subsequent refinement process to reduce artefacts introduced by demosaicking. To evaluate the performance of these measures, a tool kit was constructed with the capability of mosaicking, demosaicking and quality assessment. The experimental results demonstrated that the vector median filtering performed less well for natural images except black and white images, however the refinement step reduced the reproduction error numerically in most cases. This proved the feasibility of extending CFA demosaicking into MSFA domain.

Spectral Characterization of a Prototype SFA Camera for Joint Visible and NIR Acquisition

Multispectral acquisition improves machine vision since it permits capturing more information on object surface properties than color imaging. The concept of spectral filter arrays has been developed recently and allows multispectral single shot acquisition with a compact camera design. Due to filter manufacturing difficulties, there was, up to recently, no system available for a large span of spectrum, i.e., visible and Near Infra-Red acquisition. This article presents the achievement of a prototype of camera that captures seven visible and one near infra-red bands on the same sensor chip. A calibration is proposed to characterize the sensor, and images are captured. Data are provided as supplementary material for further analysis and simulations. This opens a new range of applications in security, robotics, automotive and medical fields.

Discrete wavelet transform based multispectral filter array demosaicking

The idea of colour filter array may be adapted to multispectral image acquisition by integrating more filter types into the array, and developing associated demosaicking algorithms. Several methods employing discrete wavelet transform (DWT) have been proposed for CFA demosaicking. In this work, we put forward an extended use of DWT for multispectral filter array demosaicking. The extension seemed straightforward, however we observed striking results. This work contributes to better understanding of the issue by demonstrating that spectral correlation and spatial resolution of the images exerts a crucial influence on the performance of DWT based demosaicking.

Optical properties of layered transition-metal halides

Near-normal incidence reflectance spectra of Fe, Co and Ni dihalides have been measured over the energy region 2-31 eV from 300 to 30 K with the use of synchrotron radiation. A complete study of the dielectric function epsilon (E), the energy-loss function -Im(1/ epsilon (E)), epsilon 0.eff(E) and Neff(E) is made for all crystals by Kramers-Kronig analysis of the optical data. The structures observed up to about 13 eV in transition-metal chlorides and bromides have been assigned to allowed charge-transfer transitions, direct excitons and valence-to-conduction band transitions. Corners and maxima are then identified in terms of direct interband transitions at the symmetry points Gamma , Z, F and L and along the symmetry line Lambda of the Brillouin zone according to the available band structure of FeCl2, CoCl2, NiCl2 and NiBr2. The identified energy gap, due to Gamma 3- to Gamma 1+ transitions at the zone centre, is found around 8.48 eV in FeCl2, 8.54 eV in CoCl2, 7.75 eV in FeBr2 and 7.82 eV in CoBr2. The saturation values of epsilon 0.eff(E) for chlorides ( approximately=3) and bromides ( approximately=4) point to a rather ionic character (fi=0.7-0.8) for all materials. Plasma resonance effects have been finally identified in the high-energy region, i.e. around 17-18 eV for the transition-metal chlorides and 16-17 eV for bromides.

An inverse display color characterization model based on an optimized geometrical structure

We have defined an inverse model for colorimetric characterization of additive displays. It is based on an optimized three-dimensional tetrahedral structure. In order to minimize the number of measurements, the structure is defined using a forward characterization model. Defining a regular grid in the device-dependent destination color space leads to heterogeneous interpolation errors in the device-independent source color space. The parameters of the function used to define the grid are optimized using a globalized Nelder-Mead simplex downhill algorithm. Several cost functions are tested on several devices. We have performed experiments with a forward model which assumes variation in chromaticities (PLVC), based on one-dimensional interpolations for each primary ramp along X, Y and Z (3×3×1-D). Results on 4 devices (2 LCD and a DLP projection devices, one LCD monitor) are shown and discussed.

Image watermarking based on a color quantization process

The purpose of this paper is to propose a color image watermarking scheme based on an image dependent color gamut sampling of the L*a*b* color space. The main motivation of this work is to control the reproduction of color images on different output devices in order to have the same color feeling, coupling intrinsic informations on the image gamut and output device calibration. This paper is focused firstly on the research of an optimal LUT (Look Up Table) which both circumscribes the color gamut of the studied image and samples the color distribution of this image. This LUT is next embedded in the image as a secret message. The principle of the watermarking scheme is to modify the pixel value of the host image without causing any change neither in image appearance nor on the shape of the image gamut.

High-end colorimetric display characterization using an adaptive training set

A new, accurate, and technology-independent display color-characterization model is introduced. It is based on polyharmonic spline interpolation and on an optimized adaptive training data set. The establishment of this model is fully automatic and requires only a few minutes, making it efficient in a practical situation. The experimental results are very good for both the forward and inverse models. Typically, the proposed model yields an average model prediction error of about 1 ∆Eab* unit or below for several displays. The maximum error is shown to be low as well. freedom given to the model considering the choice of a tar- get color space and of the kernel and smoothing factor for the interpolation. This increases noticeably the accuracy of the model. The inverse model is based on a tetrahedral in- terpolation, using a grid designed in RGB. As design goals, we aim for the display color-characterization model to be as accurate as possible on any type of display and we want the color correction to be done in real time (no pre-processing). Moreover, we want the model establishment not to exceed a practical time of a few minutes (the time of a coffee break). We first present the state of the art of display color characterization in Sec. 2. We then introduce our new accu- rate display color-characterization model. We evaluate this method experimentally on different displays. Before con- cluding, we describe briefly its application to multispectral image real-time color rendering under a virtual illumination through its GPU implementation.

Illuminant estimation in multispectral imaging

With the advancement in sensor technology, the use of multispectral imaging is gaining wide popularity for computer vision applications. Multispectral imaging is used to achieve better discrimination between the radiance spectra, as compared to the color images. However, it is still sensitive to illumination changes. This study evaluates the potential evolution of illuminant estimation models from color to multispectral imaging. We first present a state of the art on computational color constancy and then extend a set of algorithms to use them in multispectral imaging. We investigate the influence of camera spectral sensitivities and the number of channels. Experiments are performed on simulations over hyperspectral data. The outcomes indicate that extension of computational color constancy algorithms from color to spectral gives promising results and may have the potential to lead towards efficient and stable representation across illuminants. However, this is highly dependent on spectral sensitivities and noise. We believe that the development of illuminant invariant multispectral imaging systems will be a key enabler for further use of this technology.

Energy balance in single exposure multispectral sensors

Recent simulations of multispectral sensors are based on a simple Gaussian model, which includes filters transmittance and substrate absorption. In this paper we want to make the distinction between these two layers. We discuss the balance of energy by channel in multispectral solid state sensors and propose an updated simple Gaussian model to simulate multispectral sensors. Results are based on simulation of typical sensor configurations.