文档介绍：Cluster-Based Feature Extraction and Data Fusion in The Wavelet
Domain
Johannes R. Sveinsson, Magnus Orn Ulfarsson and Jon Atli Benediktsson
Department of Electrical puter Engineering, University of Iceland,
Hjardarhagi 2-6, Reykjavik, 1S-107, Iceland
E-mail: , , and benedikt(
ABSTRACT not lead to a significant decrease in overall classification
accuracy pared to the one obtained in the origi-
This paper will concentrate on linear feature extraction
nal feature space. In this paper linear feature extraction
methods for work classifiers. The considered
method, based on cluster-based feature extraction of the
feature extraction method is based on discrete wavelet
wavelet coefficients for works classifiers are dis-
transformations (.DWTS) and cluster-based procedure, .,
cussed and applied in classification of multisource remote
cluster-based feature extraction of the wavelet coefficients
sensing and geographic data. The method is an extension
of remote sensing and geographic data is considered. The
to a method proposed by Pittner and Kamarthi [3].
cluster-based feature extraction is a preprocessing routine
putes feature-vectors to group the wavelet coeff-
icients in an unsupervised way. These feature-vectors are 2. FEATURE EXTRACTION
then used as a mask or a filter for the selection of rep-
resentativ