Add to ORKGThe maximum entropy principle has a relevant role in image processing, in particular for thresholding and image segmentation. Different entropic formulations are available to this purpose; one of them is based on the Tsallis non-extensive entropy. Here, we propose a discussion of its use for bi-and multi-level thresholding
Este trabalho faz um estudo do uso da entropia como ferramenta para o reconhecimento de padrões em i...
This paper compares the effectiveness of the Tsallis entropy over the classic Boltzmann-Gibbs-Shanno...
In this dissertation, we discuss multi-level image thresholding techniques based on information theo...
The maximum entropy principle has a relevant role in image processing, in particular for thresholdin...
The maximum entropy principle is often used for bi-level or multi-level thresholding of images. For ...
The maximum entropy principle is largely used in thresholding and segmentation of images. Among the ...
The maximum entropy principle is often used for bi-level or multi-level thresholding of images. For ...
In image processing, the maximum entropy principle is often used for the elaboration of images, in p...
In image processing, the maximum entropy principle is generally recognized as having a relevant role...
The Boltzmann–Gibbs and Tsallis entropies are essential concepts in statistical physics, which have ...
Renyi entropy based image thresholding in [Sahoo, P., Wilkins, C., et al., 1997. Thresholding select...
This paper deals with an entropic approach as unsupervised thresholding technique for image processi...
Vol. IInternational audienceThis paper deals with an entropic approach as unsupervised thresholding ...
Entropy has a relevant role in several applications of information theory and in the image processin...
International audienceThis paper deals with an entropic approach as unsupervised thresholding techni...
Este trabalho faz um estudo do uso da entropia como ferramenta para o reconhecimento de padrões em i...
This paper compares the effectiveness of the Tsallis entropy over the classic Boltzmann-Gibbs-Shanno...
In this dissertation, we discuss multi-level image thresholding techniques based on information theo...
The maximum entropy principle has a relevant role in image processing, in particular for thresholdin...
The maximum entropy principle is often used for bi-level or multi-level thresholding of images. For ...
The maximum entropy principle is largely used in thresholding and segmentation of images. Among the ...
The maximum entropy principle is often used for bi-level or multi-level thresholding of images. For ...
In image processing, the maximum entropy principle is often used for the elaboration of images, in p...
In image processing, the maximum entropy principle is generally recognized as having a relevant role...
The Boltzmann–Gibbs and Tsallis entropies are essential concepts in statistical physics, which have ...
Renyi entropy based image thresholding in [Sahoo, P., Wilkins, C., et al., 1997. Thresholding select...
This paper deals with an entropic approach as unsupervised thresholding technique for image processi...
Vol. IInternational audienceThis paper deals with an entropic approach as unsupervised thresholding ...
Entropy has a relevant role in several applications of information theory and in the image processin...
International audienceThis paper deals with an entropic approach as unsupervised thresholding techni...
Este trabalho faz um estudo do uso da entropia como ferramenta para o reconhecimento de padrões em i...
This paper compares the effectiveness of the Tsallis entropy over the classic Boltzmann-Gibbs-Shanno...
In this dissertation, we discuss multi-level image thresholding techniques based on information theo...