Image compression using data-dependent triangulations

Authors:
Burkhard Lehner;Georg Umlauf;Bernd Hamann
Affiliations:
Department of Computer Science, University of Kaiserslautern, Germany;Department of Computer Science, University of Kaiserslautern, Germany;Institute for Data Analysis and Visualization and Department of Computer Science, University of California, Davis
Venue:
ISVC'07 Proceedings of the 3rd international conference on Advances in visual computing - Volume Part I
Year:
2007

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Abstract

We present a method to speed up the computation of a high-quality data-dependent triangulation approximating an image using simulated annealing by probability distributions guided by local approximation error and its variance. The triangulation encodes the image, yielding compression rates comparable to or even superior to JPEG and JPEG2000 compression. The specific contributions of our paper are a speed-up of the simulated annealing optimization and a comparison of our approach to other image approximation and compression methods. Furthermore, we propose an adaptive vertex insertion/removal strategy and termination criteria for the simulated annealing to achieve specified approximation error bounds.