Abstract
Image contrast enhancement or boosting is normally referred to as one of the most crucial tasks in image processing, and histogram equalization (HE) is one of the most pervasive methods applied to address this task. HE and its variants have been proven a simple and effective technique. However, no one consistent image quality evaluation standard has been built for them, not to say other relevant approaches. In other words, it is lack of enough attention to image quality evaluation for contrast enhancement algorithms. The authors proposed a novel evaluation standard combining Gini-index and variation coefficient. They verified the effectiveness of the proposed evaluation standard especially for double plateaus histogram equalization (DPHE) algorithm. Their experimental results showed that when H and PSNR cannot clearly describe the image quality, the proposed objective standard could provide an additional objective basis for the quality evaluation of DPHE, which may be extended to pervasive image enhancement algorithms.
Similar content being viewed by others
Availability of data and materials
The database source for this paper is from http://www.cvl.isy.liu.se/en/research/datasets/ltir and http://dgp.toronto.edu/~nmorris/data, and nine infrared images are chosen, as shown in Fig. 2.
References
Kotkar, V.A., Gharde, S.S.: Review of various image contrast enhancement techniques. Int. J. Innov. Res. Sci. Eng. Technol. 2(7), 2786–2793 (2013)
Wigner, E.P.: Theory of traveling-wave optical laser. Phys. Rev. 134, A635–A646 (1965)
Gonzalez, R.C., Woods, R.E.: Digital Image Processing. Prentice Hall, Upper Saddle River (2002)
Fardel, R., Nagel, M., Nuesch, F., Lippert, T., Wokaun, A.: Fabrication of organic light emitting diode pixels by laser-assisted forward transfer. Appl. Phys. Lett. 91(6), 061103 (2007)
Silverman, J.: Signal-processing algorithms for display and enhancement of IR images. Infrared Technology XIX. SPIE, 2020: 440–450 (1993)
Song, Y.F., Shao, X.P., Xu, J.: New enhancement algorithm for infrared image based on double plateaus histogram. Infrared Laser Eng. 37(2), 308–311 (2008)
Filliben, J.J.: The probability plot correlation coefficient test for normality. Technometrics 17(1), 111–117 (1975)
Chabrier, S., Emile, B., Rosenberger, C., et al.: Unsupervised performance evaluation of image segmentation. EURASIP J. Adv. Signal Process. 2006, 1–12 (2006)
Jourlin, M., Pinoli, J.C., Zeboudj, R.: Contrast definition and contour detection for logarithmic images. J. Microsc. 156(1), 33–40 (1989)
Lerman, R.I., Yitzhaki, S.: A note on the calculation and interpretation of the Gini index. Econ. Lett. 15(3–4), 363–368 (1984)
Abdi, H.: Congruence: Congruence coefficient, RV coefficient, and mantel coefficient. Encycl. Res. Des. 3, 222–229 (2010)
Vijayalakshmi, D., Nath, M.K., Acharya, O.P.: A comprehensive survey on image contrast enhancement techniques in spatial domain. Sens. Imaging 21(1), 40 (2020)
Kun, L., Yong, Ma., Yue, X., et al.: A new adaptive contrast enhancement algorithm for infrared images based on double plateaus histogram equalization. Infrared Phys. Technol. 55(4), 309–315 (2012)
Cho, H., Hachtel, G.D., Macii, E., et al.: Algorithms for approximate FSM traversal. In: Proceedings of the 30th International Design Automation Conference, pp. 25–30 (1993)
Shuo, Li., Weiqin, J., Li, Li., et al.: An improved contrast enhancement algorithm for infrared images based on adaptive double plateaus histogram equalization. Infrared Phys. Technol. 90, 164–174 (2018)
Bonacini, L., Gallo, G., Scicchitano, S.: Working from home and income inequality: risks of a ‘new normal’with COVID-19. J. Popul. Econ. 34(1), 303–360 (2021)
Habba, M., Ameur, M., Jabrane, Y.: A novel Gini index based evaluation criterion for image segmentation. Optik 168, 446–457 (2018)
Kukkonen, H., Rovamo, J., Tiippana, K., et al.: Michelson contrast, RMS contrast and energy of various spatial stimuli at threshold. Vision. Res. 33(10), 1431–1436 (1993)
Gray, S.B.: Local properties of binary images in two dimensions. IEEE Trans. Comput. 100(5), 551–561 (1971)
Zuiderveld, K.: Contrast limited adaptive histogram equalization. Graphics Gems, pp. 474–485. Academic Press Professional Inc, USA (1994).
Ye, Z.: Objective assessment of nonlinear segmentation approaches to gray level underwater images. Int. J. Graphics Vis. Image Process. (GVIP) 9(II), 39–46 (2009)
Isa, I.S., Sulaiman, S.N., Mustapha, M., et al.: Automatic contrast enhancement of brain MR images using average intensity replacement based on adaptive histogram equalization (AIR-AHE). Biocybern. Biomed. Eng. 37(1), 24–34 (2017)
Pizer, S.M., Amburn, E.P., Austin, J.D., et al.: Adaptive histogram equalization and its variations. Comput. Vis. Graph. Image Process. 39(3), 355–368 (1987)
Acknowledgements
The authors would like to thank anonymous reviewers for their kind and valuable comments.
Funding
This manuscript received July 02, 2023; accepted July 28, 2023. This work was supported in part by National Science Foundation of China under Grant 61072135, 81971702, the Fundamental Research Funds for the Central Universities under Grant 2042017gf0075, 2042019gf0072, and Natural Science Foundation of Hubei Province under Grant 2017CFB721. Asterisk indicates corresponding author.
Author information
Authors and Affiliations
Contributions
li weiming wrote the main manuscript text. All authors reviewed the manuscript.
Corresponding author
Ethics declarations
Conflict of interest
The authors declare no competing interests.
Ethical approval
There are no ethical issues with this paper.
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
About this article
Cite this article
Li, W., Jiang, X. A novel evaluation standard combining gini-index and variation coefficient for double plateaus histogram equalization. SIViP 18, 3321–3328 (2024). https://doi.org/10.1007/s11760-024-02995-8
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s11760-024-02995-8