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Fusing Features in Direct Volume Rendered Images

  • Yingcai Wu
  • Huamin Qu
  • Hong Zhou
  • Ming-Yuen Chan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4291)

Abstract

In this paper, we propose a novel framework which can fuse multiple user selected features in different direct volume rendered images into a comprehensive image according to users’ preference. The framework relies on three techniques, i.e., user voting, genetic algorithm, and image similarity. In this framework, we transform the fusing problem to an optimization problem with a novel energy function which is based on user voting and image similarity. The optimization problem can then be solved by the genetic algorithm. Experimental results on some real volume data demonstrate the effectiveness of our framework.

Keywords

Genetic Algorithm Image Similarity Edge Image Direct Volume Fuse Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Yingcai Wu
    • 1
  • Huamin Qu
    • 1
  • Hong Zhou
    • 1
  • Ming-Yuen Chan
    • 1
  1. 1.Department of Computer Science and EngineeringHong Kong University of Science and Technology 

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