In image processing, the maximum entropy principle is often used for the elaboration of images, in particular to distinguish in them the objects from the background, through a process of image segmentation. Different formulations of the image entropy are available to this purpose, but the most prominent in recent publications, in particular in those concerning the medical image processing, is that of the Tsallis non-extensive entropy. Here, we discuss and show some examples of segmentation with this specific entropy.
The Tsallis Entropy and the Segmentation of Images / Sparavigna, Amelia Carolina. - ELETTRONICO. - (2016). [10.2139/ssrn.2820565]
The Tsallis Entropy and the Segmentation of Images
SPARAVIGNA, Amelia Carolina
2016
Abstract
In image processing, the maximum entropy principle is often used for the elaboration of images, in particular to distinguish in them the objects from the background, through a process of image segmentation. Different formulations of the image entropy are available to this purpose, but the most prominent in recent publications, in particular in those concerning the medical image processing, is that of the Tsallis non-extensive entropy. Here, we discuss and show some examples of segmentation with this specific entropy.Pubblicazioni consigliate
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https://hdl.handle.net/11583/2647234
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