Visualization of 2DWave Propagation by Huygens' Principle

We present a novel technique to visualize wave propagation in 2D scalar fields. Direct visualization of wave fronts is susceptible to visual clutter and interpretation difficulties due to space-time interference and global influence. To avoid this, we employ Huygens' principle to obtain virtual sources that provide a concise space-time representation of the overall dynamics by means of elementary waves. We first demonstrate the utility of our overall approach by computing a dense field of virtual sources. This variant offers full insight into space-time wave dynamics in terms of elementary waves, but it reflects the full problem of inverse wave propagation and hence suffers from high costs regarding memory consumption and computation. As an alternative, we therefore provide a less accurate and less generic but more efficient approach. This alternative performs wave front extraction with subsequent Hough transform to identify potential virtual sources. We evaluate both approaches and demonstrate their strengths and weaknesses by means of a GPU-based prototype and an implementation on a Cray XC40 supercomputer, using data from different domains.

[1]  A. Tikhonov,et al.  Numerical Methods for the Solution of Ill-Posed Problems , 1995 .

[2]  E. H. Linfoot Principles of Optics , 1961 .

[3]  Albert Tarantola,et al.  Inverse problem theory - and methods for model parameter estimation , 2004 .

[4]  Eric J. Kelmelis,et al.  CULA: hybrid GPU accelerated linear algebra routines , 2010, Defense + Commercial Sensing.

[5]  Harald Obermaier,et al.  On Mesh-Free Valley Surface Extraction with Application to Low Frequency Sound Simulation , 2012, IEEE Transactions on Visualization and Computer Graphics.

[6]  Herbert Edelsbrunner,et al.  Topological persistence and simplification , 2000, Proceedings 41st Annual Symposium on Foundations of Computer Science.

[7]  Filip Sadlo,et al.  Efficient Visualization of Lagrangian Coherent Structures by Filtered AMR Ridge Extraction , 2007, IEEE Transactions on Visualization and Computer Graphics.

[8]  David H. Eberly,et al.  Ridges in Image and Data Analysis , 1996, Computational Imaging and Vision.

[9]  Richard O. Duda,et al.  Use of the Hough transformation to detect lines and curves in pictures , 1972, CACM.

[10]  Steven G. Johnson,et al.  The Design and Implementation of FFTW3 , 2005, Proceedings of the IEEE.

[11]  Hans Hagen,et al.  Comparative Visualization for Wave-based and Geometric Acoustics , 2006, IEEE Transactions on Visualization and Computer Graphics.