NDLI: An efficient wavelet dictionary for texture separation

Content Provider	IEEE Xplore Digital Library
Author	Loghmari, M.A. Katlane, F. Naceur, M.S.
Copyright Year	2007
Description	Author affiliation: Ecole Nat. d'lngenieurs de Tunis, Tunis le Belvedere (Loghmari, M.A.; Katlane, F.; Naceur, M.S.)
Abstract	In this paper, our goal is to highlight the importance of the source separation method on remote sensing data analysis when dealing with urban areas characterized by spatial concept like texture. Source separation has become an attractive tool used to compensate physical information deficiency by statistical assumptions. The method's key comes from the fact that the blind signal separation can be achieved by restoring statistical independence. In this work, we try to design a statistical generative model, based on a wavelet dictionary, composed of atoms which are automatically selected to maximize the sparseness of the underlying texture type. This application is of utmost importance in the classification process and should minimize the misclassification risk of urban areas.
Starting Page	266
Ending Page	269
File Size	400875
Page Count	4
File Format	PDF
ISBN	9781424412112
DOI	10.1109/IGARSS.2007.4422781
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-07-23
Publisher Place	Spain
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Dictionaries Source separation Vectors Blind source separation Wavelet analysis Remote sensing Data analysis Urban areas Signal restoration Signal processing texture analysis source separation wavelets
Content Type	Text
Resource Type	Article

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