Academic literature on the topic 'Color rendition accuracy'

The paper presents the study results of paper trapping during inkjet printing which contains cellulose pulp from the inner bark layer of mulberry branches. The connection between the print density and the paper surface structure, in particular, water absorption and raggedness, is established. The study of the stepwise gradation transition and color rendition, the graphic accuracy of reproduction of the slur element of the image is carried out. Densitometric and microscopic analysis of the impressions printed on an inkjet printer was performed. It was revealed that the pigments of water ink, depending on the microgeometry of the paper surface, penetrated deeper in different ways. It was found that the maximum thickness of the paint layer, expressed using the optical density values for the primary colors of the subtractive synthesis, and the best color reproduction were provided by the surface of the paper sample with 100 % addition of cellulose pulp from the inner layer of the bark of mulberry tree branches, which has the least roughness, according to the scanning probe microscope Solver HV. Recommendations are given for testing paper data on inkjet printers that use pigment inks and are less demanding on the surface properties of paper, or by printing methods that do not use low-viscosity printing inks.

Luminance measurements are used in a vast range of lighting technology fields. The author’s research has proved that measuring the luminance distribution on light source surface is the most challenging part of this process. The research has been conducted for a commercially available digital luminance distribution meter, with the goal of analyzing the influence of image focus settings and exposure parameters on the measured luminance values. It has been concluded that the incorrect image focus and inadequately matched exposure parameters (distance from the workpiece) contribute to quantitative changes in the information on luminance distribution on the LED surface and affect the precision the maximum luminance determination. Full Text: PDF ReferencesC. Xu, H. Cheng, and Y. Feng, "Optical design of rectangular illumination with freeform lenses for the application of LED road lighting," Frontiers of Optoelectronics, 2017, CrossRef D. Czyzewski, "LED substitutes of conventional incandescent lamps," Przeglad Elektrotechniczny, vol. 88, no. 11A, pp. 123-127, 2012. DirectLink W. R. Ryckaert, K. A. G. Smet, I. A. A. Roelandts, M. Van Gils, and P. Hanselaer, "Linear LED tubes versus fluorescent lamps: An evaluation," Energy and Buildings, 2012, CrossRef X.-H. Lee, I. Moreno, and C.-C. Sun, "High-performance LED street lighting using microlens arrays," Optics Express, 2013, CrossRef D. Czyzewski, "The street lighting luminaires with LEDs," Przeglad Elektrotechniczny, vol. 86, pp. 276-279, 2009. DirectLink D. Mozyrska, M. Wyrwas, and I. Fryc, "The determination of the LEDs colorimetric parameters, in the range of their operating temperature," Przeglad Elektrotechniczny, vol. 93, no. 4a, pp. 232-234, 2012. DirectLink J. Kowalska and I. Fryc, "Colour rendition quality of typical fluorescent lamps determined by CIE colour fidelity index and colour rendering index," Przeglad Elektrotechniczny, vol. 95, no. 7, pp. 94--97, 2019, CrossRef J. Kowalska, "Analysis of parameters describing the quality of the color rendering of light sources according to the IES TM-30-15 and the CIE 013.3-1995," Przeglad Elektrotechniczny, vol. 93, no. 6, pp. 50--54, 2017, CrossRef K. Houser, M. Mossman, K. Smet, and L. Whitehead, "Tutorial: Color Rendering and Its Applications in Lighting," LEUKOS - Journal of Illuminating Engineering Society of North America, vol. 12, no. 1-2, pp. 7-26, 2016, CrossRef S. Słomiński, "Identifying problems with luminaire luminance measurements for discomfort glare analysis," Lighting Research and Technology, 2016, CrossRef D. Czyzewski, "Investigation of COB LED luminance distribution," 2016, CrossRef M. Jongewaard, "Guide to selecting the appropriate type of light source model," in Proc.SPIE, Aug. 2002, vol. 4775, CrossRef D. Czyzewski, "Selected problems of defining the luminous area of electroluminescent diodes," Przeglad Elektrotechniczny, vol. R. 84, nr 8, pp. 125-128, 2008. DirectLink C. D. Galatanu, "Improving the Luminance Measurement from Digital Images," in 2019 International Conference on Electromechanical and Energy Systems (SIELMEN), 2019, pp. 1-4. CrossRef I. Fryc and E. Czech, "Application of optical fibers and CCD array for measurement of luminance distribution," in Proc. SPIE 5064, Lightmetry 2002: Metrology and Testing Techniques Using Light, 2003, pp. 18-21, CrossRef I. Fryc and E. Czech, "Spectral correction of the measurement CCD array," Optical Engineering, 2002, CrossRef I. Fryc, "Angular characteristics of a silicon detector spectral sensitivity corrected by an absorption filter," in Proc. SPIE 4517, Lightmetry: Metrology, Spectroscopy, and Testing Techniques Using Light, 2001, pp. 42-45, CrossRef I. Fryc, "Accuracy of spectral correction of a CCD array for luminance distribution measurement," in Proc. SPIE 5064, Lightmetry 2002: Metrology and Testing Techniques Using Light, 2003, pp. 38-42, CrossRef M. Moeck and S. Anaokar, "Illuminance analysis from high dynamic range images," LEUKOS - Journal of Illuminating Engineering Society of North America, pp. 211-228, 2006, CrossRef D. Czyżewski, "Research on luminance distributions of chip-on-board light-emitting diodes," Crystals, 2019, CrossRef

The image recorded by a digital camera mainly depends on three factors: the physical content of the scene, the illumination incident on the scene, and the characteristics of the camera. This leads to a problem for many applications where the main interest is in the color rendition accuracy of the scene acquired. It is known that the color reproduction accuracy of a digital imaging acquisition device is a key factor to the overall perceived image quality, and that there are mainly two modules responsible for it: the former is the illuminant estimation and correction module, the latter is the color matrix transformation. These two modules together form what may be called the color correction pipeline. This thesis has the objective to design and test new and more robust modules for the color correction pipeline, studying and exploiting the existing crosstalks in order to obtain a higher color reproduction accuracy. The first module considered is the illuminant estimation and correction one; many illuminant estimation solutions have been proposed in the last few years, although it is known that the problem addressed is actually ill-posed as its solution lack uniqueness or stability. To cope with this problem, different solutions usually exploit some assumptions about the statistical properties of the expected illuminants and/or of the object reflectances in the scene. In the last few years two research areas that are important in the context of improving the performance of color constancy algorithms have been highlighted: making additional measurements at the time of image capture (i.e. using more color pixel information), and algorithm combining (i.e. using two or more estimations of the illuminants). In this thesis a third hypothesis is investigated: the use of low level visual information to improve illuminant estimation. The second module considered is the transformation of the camera-dependent RGB image data into a standard RGB color space. This transformation, usually called color correction matrix or color matrixing, is needed because the spectral sensitivity functions of the sensor color channels rarely match those of the desired output color space (usually sRGB). The color correction matrix transformation is usually optimized assuming that the illuminant in the scene has been successfully estimated and compensated for. Both the illuminant estimation process and the color correction matrix concur in the formation of the overall perceived image quality. The two processes have always been studied separately, thus ignoring the interactions between them. In this thesis the interactions between the illuminant estimation process and the color correction matrix in the formation of the overall color accuracy are investigated, especially when the white point estimation is imperfect. How the color correction transform amplifies the illuminant estimation errors is also investigated. Furthermore, it is shown that it is possible to incorporate knowledge about the illuminant estimation behavior in the optimization of the color correction matrix to alleviate the error amplification. It is demonstrated that a fixed device chromatic response characterization, which is often adopted, is not able to produce good color accuracy in most situations. New strategies to improve color accuracy under both perfect and imperfect white point estimation are proposed, which clearly suggest that adaptive color transformations have to be preferred in order to improve the color accuracy.

Historic buildings and architectural surfaces are a significant part of the European heritage.In the field of preservation and conservation of historic facades – especially for those of buildings that are still in use - restorers frequently face the task of faithfully repurpose from a chromatic point of view surfaces and paintings, often having small patches of original color as the only reference.This step is often carried out by visual assessment by a restorer proficient in the field of colorant formulation and with in-depth knowledge of the behavior of colorants in a specific material: the process involves making a series of samples that are tested on the surface to be treated, in order to identify the most suitable.Nevertheless, such a procedure is strictly related to the sensitivity of the conservator.The series of samples produced can easily be subject to phenomena of observer metamerism and conditional match: in fact, it is possible that a set of samples that appear to match under a defined set of viewing conditions, such as light source or viewing angle, no longer match if those conditions change.Since restoration is first and foremost a science, the restorer is provided by the market with effective and specific color measurement devices that are able to capture, measure and quantify the color of a surface, providing reliable data: -in order of increasing sophistication- densitometers, colorimeters and spectrophotometers.Unfortunately, on a restoration site and scaffolding the restorer does not always have the opportunity to use such sophisticated field-portable: as such equipment is often designed for other purposes, its use in built heritage conservation usually necessitates testing and careful calibration on order to ensure accurate data.Compromises must be made: the aim of this paper is to identify an intermediate solution, which would be more effective than visual assessment, easy to perform, and significantly less expensive than portable spectrophotometers.How this will be achieved? The tool I tested for this purpose is X-Rite's Color Checker, a target specifically designed for photography and video production that is able to compare, measure and analyze differences in color reproduction in any color rendition system.I used the Color Checker target and software to compare original paintings with samples reproduced by visual assessment, in order to verify their spectral match, which means the two colors have the same color coordinates and appear identical regardless of illuminant or observer.Then, I tested my data by comparing them with those obtained by specifically designed equipment.The results show that this method is able to provide relevant information on color matching, it is quick and easy to perform and definitely affordable, and it could represent a smart alternative for built heritage conservation.