Process Simulation Using Randomized Markov Chain and Truncated Marginal Distribution
The Journal of Supercomputing - Special issue on computational issues in fluid dynamics optimization and simulation
Efficient Random Process Generation for Reliable Simulation of Complex Systems
ICCS '01 Proceedings of the International Conference on Computational Science-Part II
Generalized method for sampling spatially correlated heterogeneous speckled imagery
EURASIP Journal on Applied Signal Processing
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The precise knowledge of the statistical properties of synthetic aperture radar (SAR) images plays a central role in their processing and analysis. These properties can be used for discriminating different types of land use, for classifying targets and for performing the assessment of algorithms and strategies throughout the use of stochastic simulation. These images seldom exhibit the well known and tractable Gaussian distribution. In this paper methods for SAR image simulation under the Gamma-distributed and correlated model are reviewed. One of these methods is carefully assessed and extended: that based on introducing correlation by means of a convolution mask applied to fields of Gaussian white noise. Results of Gamma- and K-distributed simulated images are shown.