Fast matrix inversion and determinant computation for Polarimetric Synthetic Aperture Radar

被引：6

作者：

Coelho, D. F. G. ^{[1
]}

Cintra, R. J. ^{[2
,3
]}

Frery, A. C. ^{[4
]}

Dimitrov, V. S. ^{[3
]}

机构：

[1] Univ Calgary, Grad Program Elect & Comp Engn Dept, Calgary, AB, Canada

[2] Univ Fed Pernambuco, Dept Estat, Signal Proc Grp, Recife, PE, Brazil

[3] Univ Calgary, Dept Elect & Comp Engn, Calgary, AB, Canada

[4] Univ Fed Alagoas, Lab Comp Cient & Anal Numer, Maceio, Brazil

来源：

COMPUTERS & GEOSCIENCES | 2018年 / 119卷

基金：

加拿大自然科学与工程研究理事会;

关键词：

PolSAR; Matrix inversion; Determinant; Fast algorithms; CHOLESKY DECOMPOSITION;

D O I：

10.1016/j.cageo.2018.07.002

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

This paper introduces a fast algorithm for simultaneous inversion and determinant computation of small sized matrices in the context of fully Polarimetric Synthetic Aperture Radar (PolSAR) image processing and analysis. The proposed fast algorithm is based on the computation of the adjoint matrix and the symmetry of the input matrix. The algorithm is implemented in a general purpose graphical processing unit (GPGPU) and compared to the usual approach based on Cholesky factorization. The assessment with simulated observations and data from an actual PolSAR sensor show a speedup factor of about two when compared to the usual Cholesky factorization. Moreover, the expressions provided here can be implemented in any platform.

引用

页码：109 / 114

页数：6

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