Efficient Two-Dimensional ARX Modeling

GO GLENTIS,CH SLUMP,OE HERRMANN

IEEE International Conference on Image Processing（1994）

UNIV TWENTE

被引用7|浏览7

摘要

In this paper a fast spatial adaptive algorithm is presented for the efficient least squares (LS), autoregressive exogenous (ARX), two-dimensional (2-D) modeling. Filter masks of general boundaries are allowed. Efficient space updating recursions are developed by exploiting the spatial shift invariance property of the 2-D data set.< >

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关键词

adaptive filters,adaptive signal processing,autoregressive processes,image processing,least squares approximations,parameter estimation,two-dimensional digital filters,2-D data set,2-D spectral estimation,autoregressive exogenous 2D modeling,edge detection,fast spatial adaptive algorithm,filter masks,general boundaries,image compression,image enhancement,image restoration,image sequences,least squares modeling,parameter estimation,space updating recursions,spatial shift invariance property,stochastic texture modeling,system identification,two-dimensional ARX modeling