4 March 2015 Heuristic-driven graph wavelet modeling of complex terrain
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Proceedings Volume 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014); 94431Y (2015) https://doi.org/10.1117/12.2179132
Event: Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 2014, Beijing, China
Abstract
We present a novel method for building a multi-resolution representation of large digital surface models. The surface points coincide with the nodes of a planar graph which can be processed using a critically sampled, invertible lifting scheme. To drive the lazy wavelet node partitioning, we employ an attribute aware cost function based on the generalized quadric error metric. The resulting algorithm can be applied to multivariate data by storing additional attributes at the graph’s nodes. We discuss how the cost computation mechanism can be coupled with the lifting scheme and examine the results by evaluating the root mean square error. The algorithm is experimentally tested using two multivariate LiDAR sets representing terrain surface and vegetation structure with different sampling densities.
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Teodor Cioacă, Bogdan Dumitrescu, Mihai-Sorin Stupariu, Ileana Pătru-Stupariu, Magdalena Năpărus, Ioana Stoicescu, Alexander Peringer, Alexandre Buttler, François Golay, "Heuristic-driven graph wavelet modeling of complex terrain", Proc. SPIE 9443, Sixth International Conference on Graphic and Image Processing (ICGIP 2014), 94431Y (4 March 2015); doi: 10.1117/12.2179132; https://doi.org/10.1117/12.2179132
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