Refinement for Morse decompositions of vector fields using robust critical simplexes

Longxing Kong; Xiao-an Tang; Junda Zhang; Li Wang

doi:10.1117/12.2244279

29 August 2016 Refinement for Morse decompositions of vector fields using robust critical simplexes

Longxing Kong, Xiao-an Tang, Junda Zhang, Li Wang

Proceedings Volume 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016); 100334T (2016) https://doi.org/10.1117/12.2244279
Event: Eighth International Conference on Digital Image Processing (ICDIP 2016), 2016, Chengu, China

Abstract

Topology of vector fields based on Morse decompositions has been a more numerically stable representation than the conventional trajectory-based topology. The refinement for Morse decompositions means to get the optimal results with lower computations. To address the problems in the already existing refinement methods, which contain too many empirical parameters and vague refinement objectives, this paper proposes a novel refinement method for Morse decompositions of vector fields based on a new refinement criterion using robust critical simplexes. Firstly, the critical simplexes are defined and detected by a robust manner. Secondly, the Morse sets can be classified by their regions and the detected critical simplexes. And a new refinement criterion for identifying Morse sets to refine based on the classification of Morse sets is built. Finally, the refinement flow of the proposed method is presented. Experimental results demonstrate the availability and effectiveness of the proposed method.

Citation Download Citation

Longxing Kong, Xiao-an Tang, Junda Zhang, and Li Wang "Refinement for Morse decompositions of vector fields using robust critical simplexes", Proc. SPIE 10033, Eighth International Conference on Digital Image Processing (ICDIP 2016), 100334T (29 August 2016); https://doi.org/10.1117/12.2244279

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