Clustering of Multi-image Sets Using Rényi Information Entropy

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F60076658%3A12520%2F16%3A43890405" target="_blank" >RIV/60076658:12520/16:43890405 - isvavai.cz</a>
Result on the web
<a href="http://link.springer.com/chapter/10.1007/978-3-319-31744-1_46" target="_blank" >http://link.springer.com/chapter/10.1007/978-3-319-31744-1_46</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1007/978-3-319-31744-1_46" target="_blank" >10.1007/978-3-319-31744-1_46</a>

Result language
angličtina
Original language name
Clustering of Multi-image Sets Using Rényi Information Entropy
Original language description
We propose a clustering method based on the calculation of variables derived from the ?? -dependent Rényi information entropy - a point information gain entropy ( H?H? ) and point information gain entropy density ( ???? ), which measure an information-entropic distance between two multidimensional distributions. The matrices of H?H? / ???? values as functions of the parameter ?? and a label of a multidimensional set's object are classified into groups using a standard k-means algorithm. The method is presented on two multi-image series which in the origin, the number of images in the sets, the number of image color channels, and the pixel resolution differ.
Czech name
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Czech description
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Project
Result was created during the realization of more than one project. More information in the Projects tab.
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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