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Information Theory-Based Automatic Multimodal Transfer Function Design

In this paper, we present a new framework for multimodal volume visualization that combines several informationtheoretic strategies to define both colors and opacities of the multimodal transfer function. To the best of our knowledge, this is the first fully automatic scheme to visualize multimodal data. To define the fused color, we set an information channel between two registered input data sets and, afterwards, we compute the informativeness associated with the respective intensity bins. This informativeness is used to weight the color contribution from both initial 1D transfer functions. To obtain the opacity, we apply an optimization process that minimizes the informational divergence between the visibility distribution captured by a set of viewpoints and a target distribution proposed by the user. This distribution is defined either from the data set features, from manually set importances, or from both. Other problems related to the multimodal visualization, such as the computation of the fused gradient and the histogram binning, have also been solved using new information-theoretic strategies. The quality and performance of our approach is evaluated on different data sets

This work was supported in part by the Spanish Government under Grant TIN2010-21089-C03-01, the Catalan Government under Grant 2009-SGR-643, and by SUR of DEC of Generalitat de Catalunya (Catalan Government)

IEEE

Director: Ministerio de Ciencia e Innovación (Espanya)
Generalitat de Catalunya. Agència de Gestió d’Ajuts Universitaris i de Recerca
Autor: Bramon Feixas, Roger
Ruiz Altisent, Marc
Bardera i Reig, Antoni
Boada, Imma
Feixas Feixas, Miquel
Sbert, Mateu
Resum: In this paper, we present a new framework for multimodal volume visualization that combines several informationtheoretic strategies to define both colors and opacities of the multimodal transfer function. To the best of our knowledge, this is the first fully automatic scheme to visualize multimodal data. To define the fused color, we set an information channel between two registered input data sets and, afterwards, we compute the informativeness associated with the respective intensity bins. This informativeness is used to weight the color contribution from both initial 1D transfer functions. To obtain the opacity, we apply an optimization process that minimizes the informational divergence between the visibility distribution captured by a set of viewpoints and a target distribution proposed by the user. This distribution is defined either from the data set features, from manually set importances, or from both. Other problems related to the multimodal visualization, such as the computation of the fused gradient and the histogram binning, have also been solved using new information-theoretic strategies. The quality and performance of our approach is evaluated on different data sets
This work was supported in part by the Spanish Government under Grant TIN2010-21089-C03-01, the Catalan Government under Grant 2009-SGR-643, and by SUR of DEC of Generalitat de Catalunya (Catalan Government)
Accés al document: http://hdl.handle.net/2072/295031
Llenguatge: eng
Editor: IEEE
Drets: Tots els drets reservats
Matèria: Imatge, Tècniques d’
Imaging systems
Visualització (Informàtica)
Information display systems
Títol: Information Theory-Based Automatic Multimodal Transfer Function Design
Tipus: info:eu-repo/semantics/article
Repositori: Recercat

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