Exploiting transformation-domain sparsity for fast query in multiple-point geostatistics

被引:0
|
作者
Mohammad J. Abdollahifard
Behrooz Nasiri
机构
[1] Tafersh University,Electrical Engineering Department
来源
Computational Geosciences | 2017年 / 21卷
关键词
Discrete cosine transform; Image quilting; Template matching; Transformation domain;
D O I
暂无
中图分类号
学科分类号
摘要
Multiple-point geostatistics has recently attracted significant attention for characterization of environmental variables. Such methods proceed by searching a large database of patterns obtained from a training image to find a match for a given data-event. The template-matching phase is usually the most time-consuming part of a MPS method. Linear transformations like discrete cosine transform or wavelet transform are capable of representing the image patches with a few nonzero coefficients. This sparsifying capability can be employed to speed up the template-matching problem up to hundreds of times by multiplying only nonzero coefficients. This method is only applicable to rectangular data-events because it is impossible to represent an odd-shaped data-event in a transformation domain. In this paper, the method is applied to speed up the image quilting (IQ) method. The experiments show that the proposed method is capable of accelerating the IQ method tens of times without sensible degradation in simulation results. The method has the potential to be employed for accelerating optimization-based and raster-scan patch-based MPS algorithms.
引用
收藏
页码:289 / 299
页数:10
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