Preview

«System analysis and applied information science»

Advanced search

Study of local assessments of contrast for digital images

https://doi.org/10.21122/2309-4923-2019-2-4-11

Abstract

The article study notion of the digital image contrast. Various quantitative estimates of the contrast of digital images are investigated. Comparative experimental studies of different contrast estimates were performed on two standard image databases. It is shown that the evaluation of contrast by calculating the arithmetic average or MSE values of a set of local estimates does not always coincide with the visual contrast assessment. Experimental results showed that the Weibull distribution shape parameter is a more accurate estimate of the set of local contrast estimates calculated by the BEGH, GORD, LOEN functions and correlates well with the visual contrast estimates.

About the Authors

Y. I. Golub
United Institute of Informatics Problems, National Academy of Sciences of Belarus
Belarus
Yuliya I. Golub – PhD, Associate Professor, Senior Research Fellow


F. V. Starovoitov
Belarusian National Technical University
Belarus
Fedor V. Starovoitov is a PhD student


References

1. Kratkij fotograficheskij slovar’. Pod obshhej redakciej A. A. Lapauri i V. I. Sheberstova. – M.: Iskusstvo. – 1956.

2. Artjushin L. F. Kontrast fotograficheskogo izobrazhenija // Fotokinotehnika: Jenciklopedija / Gl. red. E. A. Iofis. – M.: Sovetskaja jenciklopedija, 1981. – S.148–150.

3. Kacenelenbogen Je. D. Kontrastnosti kojefficient // Fotokinotehnika: Jenciklopedija / Gl. red. E. A. Iofis. – M.: Sovetskaja jenciklopedija, 1981. – S. 150.

4. Gordon R., Rangayyan R. M. Feature enhancement of film mammograms using fixed and adaptive neighborhoods // Applied Optics, 1984. – 23(4). – P. 560–564.

5. Kadnichanskij S. A. Ocenka kontrasta cifrovyh ajerofotoi kosmicheskih snimkov // Geodezija i kartografi – 2018. – № 3. – S. 46–51.

6. Starovojtov V. V. Utochnenie indeksa strukturnogo shodstva izobrazhenij SSIM // Informatika. – 2018. – V. 15. – № 3. – S. 7–16.

7. Starovojtov, V. V., Starovojtov F. V. Sravnitel’nyj analiz bezjetalonnyh mer ocenki kachestva cifrovyh izobrazhenij // Sistemnyj analiz i prikladnaja informatika. – 2017. – V. 13. – № 1. – S. 24–31.

8. Beghdadi, A., Le Negrate, A. Contrast enhancement technique based on local detection of edges // Computer Vision, Graphics, and Image Processing, 1989. – V. 46. – N. 2. – P. 162–174.

9. Kodak Lossless True Color Image Suite. [Online]. Available: http://r0k.us/graphics/kodak/.

10. Gu K., Zhai G., et al. Subjective and objective quality assessment for images with contrast change // Proc. IEEE Int. Conf. on Image Processing, Melbourne, VIC, Australia, Sep. 2013. – P. 383–387.

11. Golestaneh, S. A., Chandler, D. M. No-reference quality assessment of JPEG images via a quality relevance map // IEEE Signal Processing Letters. – 2014. – V. 21. – N. 2. – P. 155–158.

12. Matkovic K. et al. Global Contrast Factor – a New Approach to Image Contrast // Computational Aesthetics, 2005. – P. 159–168.


Review

For citations:


Golub Y.I., Starovoitov F.V. Study of local assessments of contrast for digital images. «System analysis and applied information science». 2019;(2):4-11. (In Russ.) https://doi.org/10.21122/2309-4923-2019-2-4-11

Views: 1194


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.


ISSN 2309-4923 (Print)
ISSN 2414-0481 (Online)