Abstract
Most of the widely used contrast enhancement methods are based on the grey level/intensity histogram of the image, as these methods are simple and easy to understand. Due to their dependency only on the frequency of grey levels, histogram-based methods generally have less time complexity and are easy to implement. The dependency only on the frequency of grey level may cause the over enhancement in the extreme grey levels/intensity regions (dark and bright regions), and increase the noise and artifacts in these regions. Also, highly frequent grey levels are most influential in the histogram-based contrast enhancement methods and hence cause over-enhancement. To deal with these drawbacks we suggest a new idea based on the entropy curve of the image that uses the complete information associated with each grey level/intensity level instead of depending on only the frequency of the grey levels. Also, a clipping criteria is applied on the entropy curve to reduce the weightage of the highly frequent grey levels, which helps to reduce the over-enhancement. A comprehensive qualitative and quantitative analysis, where quantitative analysis is performed using SSIM, GMSD, VSI, and PSNR parameters, shows that the performance of the proposed method is better than most of the existing contrast-enhancement tools. It produces natural-looking, high-contrast images with minimal artifacts.
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This work was supported in part by the Council of Scientific and Industrial Research India (CSIR) under Grant 09/1174(0007)2019-EMR-I.
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All authors have made substantial contributions to the conception, design, and revision of the paper. Priyanshu Singh Yadav authored the manuscript and collected the data, with Bupender Gupta and Subir Singh Lamba providing manuscript review.
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Yadav, P.S., Gupta, B. & Lamba, S.S. A new approach of image contrast enhancement based on entropy curve. SIViP 18, 3431–3444 (2024). https://doi.org/10.1007/s11760-024-03009-3
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DOI: https://doi.org/10.1007/s11760-024-03009-3