Hierarchical image representation simplification driven by region complexity

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Abstract

This article presents a technique that arranges the elements of hierarchical representations of images according to a coarseness attribute. The choice of the attribute can be made according to prior knowledge about the content of the images and the intended application. The transformation is similar to filtering a hierarchy with a non-increasing attribute, and comprises the results of multiple simple filterings with an increasing attribute. The transformed hierarchy can be used for search space reduction prior to the image analysis process because it allows for direct access to the hierarchy elements at the same scale or a narrow range of scales. © 2013 Springer-Verlag.

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APA

Bosilj, P., Lefèvre, S., & Kijak, E. (2013). Hierarchical image representation simplification driven by region complexity. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8156 LNCS, pp. 562–571). https://doi.org/10.1007/978-3-642-41181-6_57

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