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ARTICLE

Gamma Correction for Brightness Preservation in Natural Images

Navleen S Rekhi1,2,*, Jagroop S Sidhu2, Amit Arora2
1 IKG Punjab Technical University, Kapurthala, Punjab, India
2 DAV Institute of Engineering & Technology, Jalandhar, 144008, Punjab, India
* Corresponding Author: Navleen S Rekhi. Email:

Computer Systems Science and Engineering 2023, 44(3), 2791-2807. https://doi.org/10.32604/csse.2023.026976

Received 07 January 2022; Accepted 30 March 2022; Issue published 01 August 2022

Abstract

Due to improper acquisition settings and other noise artifacts, the image degraded to yield poor mean preservation in brightness. The simplest way to improve the preservation is the implementation of histogram equalization. Because of over-enhancement, it failed to preserve the mean brightness and produce the poor quality of the image. This paper proposes a multi-scale decomposition for brightness preservation using gamma correction. After transformation to hue, saturation and intensity (HSI) channel, the 2D- discrete wavelet transform decomposed the intensity component into low and high-pass coefficients. At the next phase, gamma correction is used by auto-tuning the scale value. The scale is the modified constant value used in the logarithmic function. Further, the scale value is optimized to obtain better visual quality in the image. The optimized value is the weighted distribution of standard deviation-mean of low pass coefficients. Finally, the experimental result is estimated in terms of quality assessment measures used as absolute mean brightness error, the measure of information detail, signal to noise ratio and patch-based contrast quality in the image. By comparison, the proposed method proved to be suitably remarkable in retaining the mean brightness and better visual quality of the image.

Keywords

Natural and aerial images; wavelet transform; gamma correction; brightness preservation

Cite This Article

N. S. Rekhi, J. S. Sidhu and A. Arora, "Gamma correction for brightness preservation in natural images," Computer Systems Science and Engineering, vol. 44, no.3, pp. 2791–2807, 2023.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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