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Journals / Hacettepe Journal of Mathematics and Statistics / 2026 / Volume: 55 Issue: 5

The impact of the entropy parameter in generalized information measures for image quality assessment

Princy T(Cochin University of Science and Technology)0000-0002-2758-622X
Nıcy Sebastian(Department of Statistics, St Thomas College, Thrissur)0000-0001-8223-7834
Pages
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Publication Date
2026-10-28
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Experimental results show that the entropy parameter q effectively captures variations in image degradation and structural characteristics.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:We introduce and study Mathai’s cumulative residual entropy, a generalized entropy measure motivated by Mathai’s entropy.
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Key Findings & Data:The practical applicability of the proposed measure is illustrated through texture analysis and image quality assessment framework.
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Conclusion & Impact:Experimental results show that the entropy parameter q effectively captures variations in image degradation and structural characteristics.
🔬Design:Research Article
📍Scope:Comprehensive Sample
⚙️Variables:Cumulative residual entropy · generalized entropy · image quality assessment

Abstract

We introduce and study Mathai’s cumulative residual entropy, a generalized entropy measure motivated by Mathai’s entropy. We establish fundamental properties, including finiteness, limiting behavior, and connections with existing cumulative residual entropy measures. The entropy parameter q is highlighted as a flexible mechanism for controlling sensitivity to distributional and structural features. The practical applicability of the proposed measure is illustrated through texture analysis and image quality assessment framework. Experimental results show that the entropy parameter q effectively captures variations in image degradation and structural characteristics. These findings show that the proposed Mathai’s cumulative residual entropy measure, compared with its Tsallis counterpart, provides a flexible and interpretable approach to texture analysis and blind image quality assessment.

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Cite This Article

T, P., Sebastian, N. (2026). The impact of the entropy parameter in generalized information measures for image quality assessment. Hacettepe Journal of Mathematics and Statistics, Volume: 55 Issue: 5. https://doi.org/10.15672/hujms.1868733

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