1 January 2006 Nonextensive information-theoretic measure for image edge detection
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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 . Submission:
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