Language and Information Content
نویسنده
چکیده
This lecture discusses the role of language and information theory concepts for data compression and solving the inverse problem. The concept of Algorithmic Information Content (AIC) is introduced and shown to be crucial to achieving optimal data compression and optimized Bayesian priors for image reconstruction. The dependence of the AIC on the selection of language then suggests how e±cient coordinate systems for the inverse problem may be selected. This motivates the selection of a multiresolution language for the reconstruction of generic images.
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