A.R. Conn, Nick Gould, et al.
Mathematics of Computation
In this paper, we present a novel approach to compression of two-dimensional Gaussian random fields. We build upon a circulant embedding method to effectively decompose and generate sample realisations. By employing the structure of the resulting circulant matrix we propose a truncation algorithm that controls energy through rank and values of retained spectral components. In contrast with naive truncation, such construction ensures that the covariance matrix remains realisable. We discuss the properties and efficiency of the algorithm with numerical examples.
A.R. Conn, Nick Gould, et al.
Mathematics of Computation
Ligang Lu, Jack L. Kouloheris
IS&T/SPIE Electronic Imaging 2002
Fausto Bernardini, Holly Rushmeier
Proceedings of SPIE - The International Society for Optical Engineering
Da-Ke He, Ashish Jagmohan, et al.
ISIT 2007