Unsupervised Wavelet-Feature Markov Clustering Algorithm for Remotely Sensed Images

Wavelet-feature Markov clustering algorithm for the remotely sensed data is based on an accurate description of abrupt spectral features and an optimized Markov clustering in the wavelet feather space. The peak points can be captured and identified by applying wavelet transform on the expanded multi...

Full description

Bibliographic Details

Published in:	IEEE International Symposium on Signal Processing and Information Technology pp. 1 - 5
Main Author:	Wang, Zhaohui
Format:	Conference Proceeding
Language:	English
Published:	IEEE 09.12.2020
Subjects:	Clustering algorithms Correlation Euclidean distance Markov clustering Remotely sensed images Signal processing algorithms Simulated annealing Temperature sensors Wavelet Wavelet domain
ISSN:	2641-5542
Online Access:	Get full text
Tags:	Add Tag No Tags, Be the first to tag this record!