1 January 2006 Nonextensive information-theoretic measure for image edge detection
Abdessamad Ben Hamza
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Abstract
We propose a nonextensive information-theoretic measure called Jensen-Tsallis divergence, which may be defined between any arbitrary number of probability distributions, and we analyze its main theoretical properties. Using the theory of majorization, we also derive its upper bounds performance. To gain further insight into the robustness and the application of the Jensen-Tsallis divergence measure in imaging, we provide some numerical experiments to show the power of this entopic measure in image edge detection.
©(2006) Society of Photo-Optical Instrumentation Engineers (SPIE)
Abdessamad Ben Hamza "Nonextensive information-theoretic measure for image edge detection," Journal of Electronic Imaging 15(1), 013011 (1 January 2006). https://doi.org/10.1117/1.2177638
Published: 1 January 2006
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CITATIONS
Cited by 39 scholarly publications.
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KEYWORDS
Edge detection

Sensors

Image processing

Image information entropy

Image registration

Signal processing

Data modeling

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