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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主要な著者:	Winston Ewert, William A. Dembski, Robert J. Marks II
フォーマット:	Artigo
言語:	Inglês
出版事項:	Wiley 2015-12-01
シリーズ:	IET Computer Vision
主題:	meaningful information measurement algorithmic specified complexity Shannon information model Kolmogorov-Chaitin-Solomonoff information model correlated noise ASC
オンライン･アクセス:	https://doi.org/10.1049/iet-cvi.2014.0141
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