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Gray-Level Image Transitions Driven by Tsallis Entropic Index

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  • Amelia Carolina Sparavigna

Abstract

The maximum entropy principle is largely used in thresholding and segmentation of images. Among the several formulations of this principle, the most effectively applied is that based on Tsallis non-extensive entropy. Here, we discuss the role of its entropic index in determining the thresholds. When this index is spanning the interval (0,1), for some images, the values of thresholds can have large leaps. In this manner, we observe abrupt transitions in the appearance of corresponding bi-level or multi-level images. These gray-level image transitions are analogous to order or texture transitions observed in physical systems, transitions which are driven by the temperature or by other physical quantities.

Suggested Citation

  • Amelia Carolina Sparavigna, 2015. "Gray-Level Image Transitions Driven by Tsallis Entropic Index," International Journal of Sciences, Office ijSciences, vol. 4(02), pages 16-25, February.
    • Handle: RePEc:adm:journl:v:4:y:2015:i:2:p:16-25
    DOI: 10.18483/ijSci.621
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    1. Amelia Carolina Sparavigna, 2015. "Tsallis Entropy In Bi-level And Multi-level Image Thresholding," International Journal of Sciences, Office ijSciences, vol. 4(01), pages 40-49, January.
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    Cited by:

    1. Amelia Carolina Sparavigna, 2015. "Shannon, Tsallis And Kaniadakis Entropies In Bi-level Image Thresholding," International Journal of Sciences, Office ijSciences, vol. 4(02), pages 35-43, February.
    2. Amelia Carolina Sparavigna, 2019. "Composition Operations of Generalized Entropies Applied to the Study of Numbers," International Journal of Sciences, Office ijSciences, vol. 8(04), pages 87-92, April.

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