Measuring meaningful information in images: algorithmic specified complexity

Measuring meaningful information in images: algorithmic specified complexity

Both Shannon and Kolmogorov–Chaitin–Solomonoff (KCS) information models fail to measure meaningful information in images. Pictures of a cow and correlated noise can both have the same Shannon and KCS information, but only the image of the cow has meaning. The application of ‘algorithmic specified co...

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Bibliographic Details
Main Authors: Winston Ewert, William A. Dembski, Robert J. Marks II
Format: Article
Language:English
Published: Wiley 2015-12-01
Series:IET Computer Vision
Subjects:
meaningful information measurement
algorithmic specified complexity
Shannon information model
Kolmogorov-Chaitin-Solomonoff information model
correlated noise
ASC
Online Access:https://doi.org/10.1049/iet-cvi.2014.0141

Internet

https://doi.org/10.1049/iet-cvi.2014.0141

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