Contrast and Contrast Enhancement (in Logic of Visual Perception of Graphic Information)

Alexey Chmutin


The concept of graphic contrast and issues of digital images' contrast control are considered from the viewpoint of visual perception of graphic information. Roles of color and contrast as its carriers are compared. The priority of the second attribute is shown. However, while color is always visible by definition, contrast can be latent. Contrast enhancement is studied in the context of detection of latent information. Being caused by perception of compared colors, informative contrast is predetermined in terms of hue-saturation-brightness. For the purposes of contrast enhancement the color model HSY is entered into consideration, where the choice of hue and saturation from color model HSB/HSV; of brightness – from color model XYZ is substantiated. Each visual contrast is defined through appropriate material contrast and its visibility functions. The structure of total contrast is resulted. Minding the outlined structure, ways to control contrast are scheduled. Special cases of its realization, when total contrast degenerates to contrasts of hues, saturations or brightness, are analyzed. Algorithms, constructed according to the optically-based theoretical formulae, are tested in natural experiment with reference to each partial contrast. Along with the initial image, the results of its informative processing are presented at magnification of contrast-enhancing factor, demonstrating the transition from zero total contrast (required image fragment is latent) up to its 100% (required fragment is visible). The relation of visibility thresholds of hue-contrast, saturation-contrast and brightness-contrast for the actualized image is estimated. The purport of estimation reflects the fact that chromatic contrast enhancement can be more effective than brightness one. Moreover, be brightness (of required fragment) and brightness (of background) equal, then it would be problematic for regular contrast-enhancing toolkit of modern graphic software to reveal the latent information. While the announced tool ensures successful contrast enhancement. The new approach actually triples volume of the accessible information, received by means of contrast enhancement from the same initial image.


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Wandell B.A. The synthesis and analysis of color images. NASA Technical Memorandum 86844. – Moffett Field: Ames Research Center, 1985. 36 p.

Yu F.T.S. et al. Introduction to Information Optics. – San Diego: Academic Press, 2001. 734 p.

Burinskij E.F. Sudebnaja ekspertiza dokumentov, proizvodstvo eja i pol'zovanije eju. – SPb.: Trud, 1903. 352 s. (in Russian).

Clerk Maxwell J. On the Theory of Three Primary Colours. // The Scientific Papers of James Clerk Maxwell. Vol. 1. – Cambridge: Cambridge University Press, 1890. P. 445.

Clerk Maxwell J. On Colour Vision. // Proceedings of the Royal Institution of Great Britain. Vol. VI. – London: Clowes, 1872. P. 260.

Hubel D.H. Eye, Brain and Vision. – New York: W.H. Freeman & Co, 1988. 241 p.

Albers J. Interaction of Color. – New Haven: Yale University Press, 2013. 193 p.

Marr D.C. Vision: A Computational Investigation into the Human Representation and Processing of Visual Information. – Cambridge: Massachusetts Institute of Technology Press, 2010. 403 p.

Arnheim R. Art and visual perception. – Berkeley: California University Press, 1974. 508 p.

FED-STD-1037C. Telecommunications: Glossary of Telecommunication Terms. – Arlington: National Communications System Technology and Standards Division, 1996. 498 p.

Grassmann H. Zur Theorie der Farbenmischung. // Annalen der Physik und Chemie. 1853. Vol. LXXXIX. № 1. pp. 69-84.

Barten P.G.J. Contrast sensitivity of the human eye and its effects on image quality. – Knegsel: HV Press, 1999. 210 p.

Palmer S.E. Vision Science: Photons to Phenomenology. – Cambridge: Massachusetts Institute of Technology Press, 1999. 832 p.

Newton I. Lectiones Opticæ. – Londini: Regiæ Societatis Typographum, 1729. 368 p.

Jähne B. Digitale Bildverarbeitung. – Berlin: Springer, 2002. 618 p.

Pauli H. Proposed extension of the CIE recommendation on "Uniform color spaces, color difference equations, and metric color terms". // Journal of the Optical Society of America. 1976. Vol. 66. № 8. pp. 866–867.

Morovič J. Color Gamut Mapping. – Chichester: Wiley, 2008. 287 p.

Smith A.R. Color gamut transform pairs. Computer Graphics. 1978. Vol. 12. № 3. pp. 12–19. DOI: 10.1145/965139.807361.

Adobe Photoshop. Help and tutorials. – San Jose: Adobe Systems Incorporated, 2013. 750 p.

Newhall S.M., Nickerson D., Judd D.B. Final Report of the O.S.A. Subcommittee on the Spacing of the Munsell Colors. Journal of the Optical Society of America. 1943. Vol. Vol. 33. № 1. pp. 385-418.

Abel N.H. Beweis der Unmöglichkeit, algebraische Gleichungen von höheren Graden als dem vierten allgemein aufzulösen. // Journal für die reine und angewandte Mathematik. 1826. Vol. 1. pp. 65-84.

Weber E.H. Der Tastsinn und das Gemeingefühl. // Handwörterbuch der Physiologie. 1846. Vol. 3. № 2. 481-588.

CEI 61966-2-1. Mesure et gestion de la couleur dans les systèmes et appareils multimédia. Partie 2-1. Gestion de la couleur – Espace chromatique RVB par défault – sRVB. – Genève: CEI Edit., 1999. 54 p.

Korn G.A., Korn T.M. Mathematical Handbook for Scientists and Engineers. – Mineola: Dover Publication, 2013. 1152 p.

Olver F.W.J., Lozier D.W., Boisvert R.F., Clark C.W. NIST Handbook of Mathematical Functions. – New York: NIST and Cambridge University Press, 2010. 951 p.

Nyström D., Colorimetric and Multispectral Image Acquisition. Thesis 1289. – Linköping: LIU-Tryck, 2006. 138 p.

Bringier B., Quintard L., Larabi M.-C. Quality Assessment for CRT and LCD Color Reproduction Using a Blind Metric. // Electronic Letters on Computer Vision and Image Analysis. 2008. Vol. 7. № 3. pp. 23-35, DOI: 10.5565/rev/elcvia.181. [Online]. Available: [Accessed 26 January 2022].

Dzulkifli F.A., Mashor M.Y., Jaafar H. Identification of Suitable Contrast Enhancement Technique for Improving the Quality of Astrocytoma Histopathological Images. // Electronic Letters on Computer Vision and Image Analysis. 2021. Vol. 20. № 1. pp. 84-98. DOI: 10.5565/rev/elcvia.1256. [Online]. Available: [Accessed 26 January 2022].

Andronova N.E., Grebenyuk P.E., Chmutin A.M. Algorithm and its program realization to control the hue contrast of digital images. // Engineering Journal of Don. 2016. № 4. [Online]. Available: [Accessed 26 January 2022].

Bondar' O.V., Chmutin А.M., Chmutin M.A. Algorithm to control saturation contrast of digital images and its program realization. // Engineering Journal of Don. 2020. № 5. [Online]. Available: [Accessed 26 January 2022].

Borovkova A.O., Rvacheva O.V., Chmutin A.M. Brightness contrast enhancement technology, algorithm and its program realization. // International Journal of Open Information Technologies. 2019. V. 7. № 11. pp. 66-78. [Online]. Available:РВ.pdf. [Accessed 26 January 2022].

Chmutin A.M., Rvacheva O.V. Virtual-optic technology for manuscript expertise. // Proceedings of SPIE. 2007. Vol. 6594. pp. 65941I.1-65941I.8. DOI: 10.1117/12.725696.

Bondar' O.V., Chmutin А.M., Chmutin M.A. Color Saturation Contrast Enhancement Technology for Digital Images. // International Journal of Open Information Technologies. 2021. V. 9. № 7. pp. 93-106. [Online]. Available:РВ.pdf. [Accessed 26 January 2022].


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