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...

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Vydané v:	IEEE International Symposium on Signal Processing and Information Technology s. 1 - 5
Hlavný autor:	Wang, Zhaohui
Médium:	Konferenčný príspevok..
Jazyk:	English
Vydavateľské údaje:	IEEE 09.12.2020
Predmet:	Clustering algorithms Correlation Euclidean distance Markov clustering Remotely sensed images Signal processing algorithms Simulated annealing Temperature sensors Wavelet Wavelet domain
ISSN:	2641-5542
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