Can I read Unsupervised classification of polarimetric SAR image with dynamic clustering: An image processing approach on EtoBox?

Unsupervised classification of polarimetric SAR image with dynamic clustering: An image processing approach by Turker Ince is a Engineering article available to read on EtoBox.

What is Unsupervised classification of polarimetric SAR image with dynamic clustering: An image processing approach about?

This paper proposes a new unsupervised classification approach for automatic analysis of polarimetric synthetic aperture radar (SAR) image. Classification of the information in multi-dimensional polarimetric SAR data space by dynamic clustering is addressed as an optimization problem and two recently proposed techniques based on particle swarm optimization (PSO) are applied to find optimal (number of) clusters in a given input data space, distance metric and a proper validity index function. The first technique, so-called multi-dimensional (MD) PSO, re-forms the native structure of swarm particles in such a way that they can make inter-dimensional passes with a dedicated dimensional PSO process. Therefore, in a multi-dimensional search space where the optimum dimension is unknown, swarm particles can seek both positional and dimensional optima. Nevertheless, MD PSO is still susceptible to premature convergence due to lack of divergence. To address this problem, fractional global best formation (FGBF) technique is then presented, which basically collects all promising dimensional components and fractionally creates an artificial global-best particle (aGB) that has the potential to b

Who reads Unsupervised classification of polarimetric SAR image with dynamic clustering: An image processing approach?

Author

Turker Ince

Publisher

Elsevier Science; Elsevier ; Elsevier Ltd.; Thomson Reuters; Elsevier BV (ISSN 0965-9978)

Published

2010

Language

EN

Field

Engineering (Physical Sciences)