Non-Rigid Multi-Modal Image Registration Using Cross-Cumulative Residual Entropy
International Journal of Computer Vision
Generalized cumulative residual entropy for distributions with unrestricted supports
Research Letters in Signal Processing
On Cumulative Entropies and Lifetime Estimations
IWINAC '09 Proceedings of the 3rd International Work-Conference on The Interplay Between Natural and Artificial Computation: Part I: Methods and Models in Artificial and Natural Computation. A Homage to Professor Mira's Scientific Legacy
Symmetric deformable image registration via optimization of information theoretic measures
Image and Vision Computing
Information-theoretic analysis of brain white matter fiber orientation distribution functions
IPMI'07 Proceedings of the 20th international conference on Information processing in medical imaging
WBIR'10 Proceedings of the 4th international conference on Biomedical image registration
Apparent diffusion coefficient approximation and diffusion anisotropy characterization in DWI
IPMI'05 Proceedings of the 19th international conference on Information Processing in Medical Imaging
Some extensions of the residual lifetime and its connection to the cumulative residual entropy
Probability in the Engineering and Informational Sciences
Neuronal data analysis based on the empirical cumulative entropy
EUROCAST'11 Proceedings of the 13th international conference on Computer Aided Systems Theory - Volume Part I
Information measures based on fractional calculus
Information Processing Letters
Hi-index | 754.84 |
In this paper, we use the cumulative distribution of a random variable to define its information content and thereby develop an alternative measure of uncertainty that extends Shannon entropy to random variables with continuous distributions. We call this measure cumulative residual entropy (CRE). The salient features of CRE are as follows: 1) it is more general than the Shannon entropy in that its definition is valid in the continuous and discrete domains, 2) it possesses more general mathematical properties than the Shannon entropy, and 3) it can be easily computed from sample data and these computations asymptotically converge to the true values. The properties of CRE and a precise formula relating CRE and Shannon entropy are given in the paper. Finally, we present some applications of CRE to reliability engineering and computer vision.