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Snapshot Multi-Band Spectral and Polarization Imaging Systems
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Snapshot Multi-Band Spectral and Polarization Imaging Systems

A special issue of Sensors (ISSN 1424-8220).

Deadline for manuscript submissions: closed (31 October 2018) | Viewed by 32373

Special Issue Editors

Dr. Jean-Baptiste Thomas

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Guest Editor
Department of Computer Science, Norwegian University of Science and Technology, 2806 Gjøvik, Norway
Interests: spectral imaging; material appearance; colour imaging; computational appearance
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Jon Yngve Hardeberg

E-Mail Website
Guest Editor
The Norwegian Colour and Visual Computing Laboratory, NTNU, Norway
Interests: multispectral color imaging; print and image quality; colorimetric device characterization; cultural heritage imaging; medical imaging; appearance
Prof. Dr. Dietrich Paulus

E-Mail Website
Guest Editor
Computational Visualistics, University Koblenz-Landau, Germany
Interests: computer vision; robot vision; color and multispectral imaging; medical image processing

Special Issue Information

Dear Colleagues,

Methods and technologies for snapshot, multi-band, spectral and polarization imaging have been researched for several decades, and, in recent years, systems have also been made commercially available.

By “snapshot, multi-band, spectral and polarization imaging”, we think mostly about optical image sensors embedded in a camera-type device, which provide an instantaneous capture of the scene under diverse modalities. We consider specifically multispectral, hyperspectral, polarization within the technology that provide snapshot capacity (spectral filter array, light field/plenoptic cameras, multi-camera setups, etc.). With the beginning of the commercialization of these products, there is a growing interest from end-users of these technologies to understand the nature of the information acquired, the limitations of the technology, and what future directions should be given to research. At the same time, for hardware manufacturers, as well as providers of processing and analysis systems, there is a need for standardization of acquisition and discussions on the quality aspects of such systems. In addition, a great deal of research has been carried out in the optical community to develop new modalities and technologies for optical filters in transmittance (i.e., plasmonic filters). Additionally, new application areas have appeared for such systems.

It seems that the time has come to focus a Special Issue on these topics, so that concerned persons can be aware of the different issues, achievements, and progress from different disciplines on one single issue.

Dr. Jean-Baptiste Thomas
Prof. Jon Yngve Hardeberg
Dr. Dietrich Paulus
Guest Editor

Manuscript Submission Information

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Keywords

  • Multi-band spectral and polarization imaging
  • Spectral sensors
  • Light field camera
  • Spectral filter array
  • Polarization imaging

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Published Papers (4 papers)

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Research

22 pages, 11609 KiB  
Article
Polarized Light Field Imaging for Single-Shot Reflectance Separation
by Jaewon Kim and Abhijeet Ghosh
Sensors 2018, 18(11), 3803; https://doi.org/10.3390/s18113803 - 6 Nov 2018
Cited by 6 | Viewed by 7397
Abstract
We present a novel computational photography technique for single-shot separation of diffuse/specular reflectance, as well as novel angular domain separation of layered reflectance. We present two imaging solutions for this purpose: two-way polarized light-field (TPLF) imaging and four-way polarized light-field (FPLF) imaging. TPLF [...] Read more.
We present a novel computational photography technique for single-shot separation of diffuse/specular reflectance, as well as novel angular domain separation of layered reflectance. We present two imaging solutions for this purpose: two-way polarized light-field (TPLF) imaging and four-way polarized light-field (FPLF) imaging. TPLF imaging consists of a polarized light-field camera, which simultaneously captures two orthogonal states of polarization. A single photograph of a subject acquired with the TPLF camera under polarized illumination then enables standard separation of diffuse (depolarizing) and polarization preserving specular reflectance using light-field sampling. We further demonstrate that the acquired data also enable novel angular separation of layered reflectance including separation of specular reflectance and single scattering in the polarization preserving component, as well as separation of shallow scattering from deep scattering in the depolarizing component. FPLF imaging further generalized the functionality of TPLF imaging under uncontrolled unpolarized or partially polarized illumination such as outdoors. We apply our approach for efficient acquisition of facial reflectance including diffuse and specular normal maps and novel separation of photometric normals into layered reflectance normals for layered facial renderings. We validate our proposed single-shot layered reflectance separation under various imaging conditions and demonstrate it to be comparable to an existing multi-shot technique that relies on structured lighting while achieving separation results under a variety of illumination conditions. Full article
(This article belongs to the Special Issue Snapshot Multi-Band Spectral and Polarization Imaging Systems)
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Graphical abstract

20 pages, 5949 KiB  
Article
Survey of Demosaicking Methods for Polarization Filter Array Images
by Sofiane Mihoubi, Pierre-Jean Lapray and Laurent Bigué
Sensors 2018, 18(11), 3688; https://doi.org/10.3390/s18113688 - 30 Oct 2018
Cited by 79 | Viewed by 6547
Abstract
Snapshot polarization imaging has gained interest in the last few decades. Recent research and technology achievements defined the polarization Filter Array (PFA). It is dedicated to division-of-focal plane polarimeters, which permits to analyze the direction of light electric field oscillation. Its filters form [...] Read more.
Snapshot polarization imaging has gained interest in the last few decades. Recent research and technology achievements defined the polarization Filter Array (PFA). It is dedicated to division-of-focal plane polarimeters, which permits to analyze the direction of light electric field oscillation. Its filters form a mosaicked pattern, in which each pixel only senses a fraction of the total polarization states, so the other missing polarization states have to be interpolated. As for Color or Spectral Filter Arrays (CFA or SFA), several dedicated demosaicking methods exist in the PFA literature. Such methods are mainly based on spatial correlation disregarding inter-channel correlation. We show that polarization channels are strongly correlated in images. We therefore propose to extend some demosaicking methods from CFA/SFA to PFA, and compare them with those that are PFA-oriented. Objective and subjective analysis show that the pseudo panchromatic image difference method provides the best results and can be used as benchmark for PFA demosaicking. Full article
(This article belongs to the Special Issue Snapshot Multi-Band Spectral and Polarization Imaging Systems)
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19 pages, 2378 KiB  
Article
Optimized Multi-Spectral Filter Array Based Imaging of Natural Scenes
by Yuqi Li, Aditi Majumder, Hao Zhang and M. Gopi
Sensors 2018, 18(4), 1172; https://doi.org/10.3390/s18041172 - 12 Apr 2018
Cited by 23 | Viewed by 6267
Abstract
Multi-spectral imaging using a camera with more than three channels is an efficient method to acquire and reconstruct spectral data and is used extensively in tasks like object recognition, relighted rendering, and color constancy. Recently developed methods are used to only guide content-dependent [...] Read more.
Multi-spectral imaging using a camera with more than three channels is an efficient method to acquire and reconstruct spectral data and is used extensively in tasks like object recognition, relighted rendering, and color constancy. Recently developed methods are used to only guide content-dependent filter selection where the set of spectral reflectances to be recovered are known a priori. We present the first content-independent spectral imaging pipeline that allows optimal selection of multiple channels. We also present algorithms for optimal placement of the channels in the color filter array yielding an efficient demosaicing order resulting in accurate spectral recovery of natural reflectance functions. These reflectance functions have the property that their power spectrum statistically exhibits a power-law behavior. Using this property, we propose power-law based error descriptors that are minimized to optimize the imaging pipeline. We extensively verify our models and optimizations using large sets of commercially available wide-band filters to demonstrate the greater accuracy and efficiency of our multi-spectral imaging pipeline over existing methods. Full article
(This article belongs to the Special Issue Snapshot Multi-Band Spectral and Polarization Imaging Systems)
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1214 KiB  
Article
Adaptive Residual Interpolation for Color and Multispectral Image Demosaicking
by Yusuke Monno, Daisuke Kiku, Masayuki Tanaka and Masatoshi Okutomi
Sensors 2017, 17(12), 2787; https://doi.org/10.3390/s17122787 - 1 Dec 2017
Cited by 73 | Viewed by 11080
Abstract
Color image demosaicking for the Bayer color filter array is an essential image processing operation for acquiring high-quality color images. Recently, residual interpolation (RI)-based algorithms have demonstrated superior demosaicking performance over conventional color difference interpolation-based algorithms. In this paper, we propose adaptive residual [...] Read more.
Color image demosaicking for the Bayer color filter array is an essential image processing operation for acquiring high-quality color images. Recently, residual interpolation (RI)-based algorithms have demonstrated superior demosaicking performance over conventional color difference interpolation-based algorithms. In this paper, we propose adaptive residual interpolation (ARI) that improves existing RI-based algorithms by adaptively combining two RI-based algorithms and selecting a suitable iteration number at each pixel. These are performed based on a unified criterion that evaluates the validity of an RI-based algorithm. Experimental comparisons using standard color image datasets demonstrate that ARI can improve existing RI-based algorithms by more than 0.6 dB in the color peak signal-to-noise ratio and can outperform state-of-the-art algorithms based on training images. We further extend ARI for a multispectral filter array, in which more than three spectral bands are arrayed, and demonstrate that ARI can achieve state-of-the-art performance also for the task of multispectral image demosaicking. Full article
(This article belongs to the Special Issue Snapshot Multi-Band Spectral and Polarization Imaging Systems)
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