Please use this identifier to cite or link to this item:
|Title:||Frequent and dependent connectivities|
|Authors:||GUEGUEN LIONEL; SOILLE Pierre|
|ISBN:||978-3-642-21568-1 (print), 978-3-642-21569-8 (online)|
|ISSN:||0302-9743 (print), 1611-3349 (online)|
|Type:||Articles in books|
|Abstract:||A dissimilarity measure between adjacent pixels of an image is usually determined by the intensity values of these pixels and therefore does not depend on statistics computed over the whole image domain. In this paper, new dissimilarity measures exploiting image statistics are proposed. This is achieved by introducing the notion of dissimilarity function defined for every possible pair of intensity values. Necessary conditions for generating a valid dissimilarity function are provided and a series of functions integrating image statistics are presented. For example, the joint probability of adjacent pixel values leads to the notion of frequent connectivity while the notion of dependent connectivity relies on the local mutual information. The usefulness of the proposed approach is demonstrated by a series of experiments on satellite image data.|
|JRC Institute:||Institute for the Protection and Security of the Citizen|
Files in This Item:
There are no files associated with this item.
Items in repository are protected by copyright, with all rights reserved, unless otherwise indicated.