Selected Papers from Computational Color Imaging Workshop 2022

A special issue of Journal of Imaging (ISSN 2313-433X). This special issue belongs to the section "Color, Multi-spectral, and Hyperspectral Imaging".

Deadline for manuscript submissions: closed (15 July 2022) | Viewed by 6992

Special Issue Editors


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Guest Editor
Laboratoire Hubert Curien, University Jean Monnet Saint-Etienne, F-42000 Saint-Etienne, France
Interests: material appearance; color reproduction; light scattering models

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Guest Editor
1. Department of Computer Science, Norwegian University of Science and Technology, 2815 Gjøvik, Norway
2. Faulty of Business and Informatics, Nagano University, Nagano 386-0032, Japan
Interests: multispectral imaging; material appearance; HDR image analysis
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Guest Editor
Laboratoire Hubert Curien UMR 5516, Université Jean Monnet, 42023 Saint-Étienne, France
Interests: human body pose estimation; human body tracking and trajectories estimation; environmental remote sensing; computer vision; color imaging
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Created in 2007, the Computational Color Imaging Workshop is a premier international forum on color images and advanced types of images (spectral, 3D, etc.), including their acquisition, processing, rendering, quality assessment, analysis, and reproduction. The workshop also addresses color vision and material appearance. Applications of color imaging in many fields are included, such as computer vision, health and beauty, art and design, video and display, printing and manufacturing, remote sensing, and natural sciences.

The workshop presents state-of-the-art and pioneering research in the following fields:

  • Color vision;
  • Color, spectral, 3D imaging;
  • Computer graphics;
  • Computational lighting;
  • Color image/video quality;
  • Physical modeling for color;
  • Color image reproduction;
  • Digital printing and fabrication;
  • Secured image;
  • Material appearance;
  • Color acquisition, calibration and display.

Prof. Dr. Mathieu Hébert
Prof. Dr. Shoji Tominaga
Prof. Dr. Alain Tremeau
Guest Editors

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Published Papers (3 papers)

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Research

20 pages, 13052 KiB  
Article
Use of Multispectral Microscopy in the Prediction of Coated Halftone Reflectance
by Fanny Dailliez, Mathieu Hébert, Lionel Chagas, Thierry Fournel and Anne Blayo
J. Imaging 2022, 8(9), 243; https://doi.org/10.3390/jimaging8090243 - 8 Sep 2022
Cited by 2 | Viewed by 1869
Abstract
When a print is coated with a transparent layer, such as a lamination film or a varnish layer, its color can be modified compared to the uncoated version due to multiple reflections between the layer-air interface and the inked substrate. These interreflections involve [...] Read more.
When a print is coated with a transparent layer, such as a lamination film or a varnish layer, its color can be modified compared to the uncoated version due to multiple reflections between the layer-air interface and the inked substrate. These interreflections involve a multiple-convolution process between the halftone pattern and a ring-shaped luminous halo. They are described by an optical model which we have developed. The challenge at stake is to observe the impact of the coated layer on the print spectral reflectances and see if it can be predicted. The approach is based on pictures of the print captured with a multispectral microscope that are processed through the optical model to predict the spectral pictures of the coated print. The pictures averaged on the spatial dimension led to spectral reflectances which can be compared with macroscale measurements performed with a spectrophotometer. Comparison between macroscale measurements and microscale measurements with a multispectral microscope being delicate, specific care has been taken to calibrate the instruments. This method resulted in fairly conclusive predictions, both at the macroscale with the spectral reflectances, and at the microscale with an accurate prediction of the blurring effect induced by the multi-convolutive optical process. The tests carried out showed that the optical and visual effect of a coating layer on single-ink or multi-ink halftones with various patterns can be predicted with a satisfactory accuracy. Hence, by measuring the spatio-spectral reflectance of the uncoated print and predicting the spatio-spectral reflectance of the coating print, we can predict the color changes due to the coating itself. The model could be included in color management workflows for printing applications including a finishing coating. Full article
(This article belongs to the Special Issue Selected Papers from Computational Color Imaging Workshop 2022)
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13 pages, 4421 KiB  
Article
Simple Color Calibration Method by Projection onto Retroreflective Materials
by Yusuke Nakamura and Takahiko Horiuchi
J. Imaging 2022, 8(9), 239; https://doi.org/10.3390/jimaging8090239 - 3 Sep 2022
Viewed by 1875
Abstract
Retroreflective materials have the property of directional reflection, reflecting light strongly in the direction of the light source, and have been used for road traffic signs. In recent years, retroreflective materials have been used in entertainment and industrial technologies, in combination with projection [...] Read more.
Retroreflective materials have the property of directional reflection, reflecting light strongly in the direction of the light source, and have been used for road traffic signs. In recent years, retroreflective materials have been used in entertainment and industrial technologies, in combination with projection mapping technology. In general, color calibration is important when projectors are used to control reflected colors. In this study, we investigated a simple color calibration method for retroreflective materials with a 3D shape under the condition that they are observed in the same direction as the light source. Three types of retroreflective materials with different reflective properties were used. First, to measure the reflective properties of each reflective material, the reflective material was fixed to a flat plate and rotated, while the reflected light was measured in the same direction as the light source. It was then confirmed that the reflected light intensity varied smoothly with angular change, and appropriate measurement angles were investigated based on the AIC criterion, aiming to interpolate the reflectance characteristics from a small number of measurement angles. Color calibration was performed based on the reflectance characteristics obtained from the derived measurement angles, and the experiments showed that good color calibration was possible with fewer measurements. Full article
(This article belongs to the Special Issue Selected Papers from Computational Color Imaging Workshop 2022)
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20 pages, 11391 KiB  
Article
Angle-Retaining Chromaticity and Color Space: Invariants and Properties
by Marco Buzzelli
J. Imaging 2022, 8(9), 232; https://doi.org/10.3390/jimaging8090232 - 29 Aug 2022
Cited by 4 | Viewed by 2496
Abstract
The angle-retaining color space (ARC) and the corresponding chromaticity diagram encode information following a cylindrical color model. Their main property is that angular distances in RGB are mapped into Euclidean distances in the ARC chromatic components, making the color space suitable for data [...] Read more.
The angle-retaining color space (ARC) and the corresponding chromaticity diagram encode information following a cylindrical color model. Their main property is that angular distances in RGB are mapped into Euclidean distances in the ARC chromatic components, making the color space suitable for data representation in the domain of color constancy. In this paper, we present an in-depth analysis of various properties of ARC: we document the variations in the numerical precisions of two alternative formulations of the ARC-to-RGB transformation and characterize how various perturbations in RGB impact the ARC representation. This was done empirically for the ARC diagram in a direct comparison against other commonly used chromaticity diagrams, and analytically for the ARC space with respect to its three components. We conclude by describing the color space in terms of perceptual uniformity, suggesting the need for new perceptual color metrics. Full article
(This article belongs to the Special Issue Selected Papers from Computational Color Imaging Workshop 2022)
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