Abstract- Shannon’s definition of entropy is critically examined and a new definition of classical entropy based on the exponential behavior of information-gain is proposed along with its justification. The concept is then extended to gray tone image for defining its global, local and conditional entropy. Based on these definitions four algorithms for object extraction are developed and implemented. One of these algorithms uses a Poisson distribution-based model of an ideal image. Finally, a concept of positional entropy giving an information regarding the location of an object in a scene is introduced. I
This paper introduces entropy as a feature for 1D signals. We propose as entropy measure the ratio b...
Vol. IInternational audienceThis paper deals with an entropic approach as unsupervised thresholding ...
In image processing, the maximum entropy principle is often used for the elaboration of images, in p...
Shannon's definition of entropy is critically examined and a new definition of classical entropy bas...
The definition of Shannon's entropy in the context of information theory is critically examined and ...
Abstract: The definition of Shannon's entropy in the context of infonnation theory is criticall...
Image is made of up pixels that contain some information. The dossier load of an image is measured b...
Image analysis is a fundamental task for extracting information from images acquired across a range ...
This paper presents a thorough study of different types of entropies. Application and comparison of ...
By combining a maximum conditional entropy principle with a basic equation of (Shannon) information ...
Entropy of order q (depending on the information contained in a sequence of gray levels of length q)...
The paper introduces entropy as a measure for 1D signals. We propose an entropy measure of the relat...
As entropy is more widely used in various fields, the physical concept of entropy has become more an...
In image processing, the maximum entropy principle is generally recognized as having a relevant role...
Recently, a novel concept referred to as Entropy of Primitive (EoP) has been proposed for evaluating...
This paper introduces entropy as a feature for 1D signals. We propose as entropy measure the ratio b...
Vol. IInternational audienceThis paper deals with an entropic approach as unsupervised thresholding ...
In image processing, the maximum entropy principle is often used for the elaboration of images, in p...
Shannon's definition of entropy is critically examined and a new definition of classical entropy bas...
The definition of Shannon's entropy in the context of information theory is critically examined and ...
Abstract: The definition of Shannon's entropy in the context of infonnation theory is criticall...
Image is made of up pixels that contain some information. The dossier load of an image is measured b...
Image analysis is a fundamental task for extracting information from images acquired across a range ...
This paper presents a thorough study of different types of entropies. Application and comparison of ...
By combining a maximum conditional entropy principle with a basic equation of (Shannon) information ...
Entropy of order q (depending on the information contained in a sequence of gray levels of length q)...
The paper introduces entropy as a measure for 1D signals. We propose an entropy measure of the relat...
As entropy is more widely used in various fields, the physical concept of entropy has become more an...
In image processing, the maximum entropy principle is generally recognized as having a relevant role...
Recently, a novel concept referred to as Entropy of Primitive (EoP) has been proposed for evaluating...
This paper introduces entropy as a feature for 1D signals. We propose as entropy measure the ratio b...
Vol. IInternational audienceThis paper deals with an entropic approach as unsupervised thresholding ...
In image processing, the maximum entropy principle is often used for the elaboration of images, in p...