+7 (495) 957-77-43

T-Comm_Article 2_4_2020

Извините, этот техт доступен только в “Американский Английский”. For the sake of viewer convenience, the content is shown below in the alternative language. You may click the link to switch the active language.

METHOD OF EQUAL CONTRAST COLOR SPACE CONSTRUCTION FOR A GIVEN INFORMATION VISUALIZATION SYSTEM AND CONTROL CONDITIONS

Aleksei M. Potashnikov, Moscow Technical University of Communications and Informatics, Moscow, Russia, nickmikh@gmail.com
Igor V. Vlasuyk, Moscow Technical University of Communications and Informatics, Moscow, Russia, ru3dlp@yandex.ru

Abstract
The paper analyzes the current use of equal-contrast color spaces and shows that, on the one hand, in fact, there is only one such color model of in various variations, on the other hand, there are many applications where it would be desirable to use a color model with both predefined restrictions on the complexity and, accordingly, the accuracy of matching the parameters of the visual system, and the ability to set the initial conditions of the experiment, such as, for example, adaptation conditions, field of view, various temporal parameters of test stimuli because the human visual system is characterized by a complex nonlinear multidimensional function transformation parameters of sense stimuli. The possibility of using «specialized» models ranges from optimizing the presentation of information, for example, when painting images in pseudo colors, to creating display devices with personalized parameters. The work contains a justification, taking into account the known parameters and characteristics of the human visual system, and the development of methods for conducting preliminary experimental studies, and processing the results of its application in a group of 66 subjects. Next, we consider all the stages of processing the experimental results in such a way that, if necessary, readers can perform similar processing for their experimental results obtained with the required conditions. Unlike previous attempts to create an equal-contrast color space, it was possible to obtain non-discontinuous expressions that allowed us to perform transitions from XYZ or RGB spaces to the proposed one and vice versa. The resulting color space is already used in solving practical problems of optimal color contrasting of objects, while a further area of work is the introduction of the dependence of color differentiation of parts of objects on their brightness into the model, which, however, requires a significant increase in the number of experiments.

Keywords: color space, CIE LAB, color distinguishability threshold, equal contrast space, color model, human visual system.

References

1. Hunter, Richard S., and Harold, Richard W. (1987). The Measurement of Appearance, 2nd ed., John Wiley and Sons, Inc. New York, NY USA.
2. CIE International Commission on Illumination, Recommendations on Uniform Color Spaces, Color-Difference Equations, Psychometric Color Terms, Supplement No. 2 to CIE Publication No. 15, Colorimetry, 1971 and 1978.
3. Gaurav Sharma, Wencheng Wu, Edul N. Dalal. (2005). The CIEDE2000 Color-Difference Formula: Implementation Notes, Supplementary Test Data, and Mathematical Observation, COLOR research and application, Vol. 30, Num. 1, Feb. 2005.
4. Mark D. Fairchild. (2004). Color appearance models. Munsell color science laboratory Rochester Institute of Technology, USA. 437 p.
5. Vlasyuk I.V. (2009). Development of a model of the human visual system for the method of objective quality control of images in digital television systems. T-Comm. No. 5, pp. 189-191.
6. Bezrukov V.N. (1976). On some features of the characteristics of the visual system of an observer of television images. Proceedings of educational institutes of communication. No. 74, pp. 28-36.
7. Eye, Brain, and Vision, David H. Hubel. (1988). Vol. 22, Scientific American Library, distributed by W. H. Freeman & Co., New York. 240 p.
8. Recommendation ITU-R BT.500-13 [Methodology for the subjective assessment of the quality of television pictures [electronic resource] Access mode: https://www.itu.int/dms_pubrec/itu-r/rec/bt/R-REC-BT.500-13-201201-I!!PDF-R.pdf
9. I.V. Vlasuyk, A.M. Potashnikov, S.G. Romanov and A.V. Balobanov. (2019). Synthesis of the Perceptionally Linear Color Space Using Machine Learning Methods. 2019 Systems of Signals Generating and Processing in the Field of on Board Communications, Moscow, Russia, pp. 1-7.