Fast calculation of Adaptive-Non-Negative-Eigenvalue-Decomposition employing particle swarm Optimization

Author

Moriyama, Takumi

Author_Institution

Grad. Sch. of Eng., Nagasaki Univ., Nagasaki, Japan

fYear

2013

Firstpage

571

Lastpage

572

Abstract

This paper considers a fast calculation of adaptive-non-negative eigenvalue-decomposition (ANNED). ANNED is one of useful polarimetric decomposition techniques and provides valuable information for remote sensing from measured covariance matrix. It has a disadvantage to take long time to estimate the decomposition parameters. To overcome this problem, the generalized eigenvalue problem has been applied. However, in practical use, more speed up is needed. In this paper, a particle swarm optimization (PSO) is applied to ANNED with the generalized eigenvalue problem. Thus, more fast calculation of ANNED is achieved and it is possible that POLSAR image with many pixels is analyzed.

Keywords

covariance matrices; eigenvalues and eigenfunctions; geophysical image processing; particle swarm optimisation; radar imaging; radar polarimetry; remote sensing by radar; synthetic aperture radar; terrain mapping; ANNED; POLSAR image; adaptive-nonnegative-eigenvalue-decomposition; covariance matrix; generalized eigenvalue problem; particle swarm optimization; polarimetric decomposition parameters; polarimetric decomposition techniques; remote sensing; Adaptation models; Covariance matrices; Eigenvalues and eigenfunctions; Particle swarm optimization; Scattering; Solid modeling; Synthetic aperture radar;

fLanguage

English

Publisher

ieee

Conference_Titel

Synthetic Aperture Radar (APSAR), 2013 Asia-Pacific Conference on

Type

conf

Filename

6705147