Title :
Texture characterization via sub-band predictive models
Author :
Stan, S. ; Datcu, M.
Author_Institution :
Remote Sensing Data Centre, German Aerosp. Centre, Wessling, Germany
Abstract :
Textural information can efficiently describe the content of a remote sensing image. In this paper we present the characterization of textures via a conditional probability model for the magnitudes of the wavelet coefficients. We select the optimal model complexity using the Bayesian formalism. The order of the model and the associated model parameters can be used for texture segmentation and classification, or as an index in an image database for content-based retrieval
Keywords :
Bayes methods; computational complexity; geophysical signal processing; image texture; remote sensing; wavelet transforms; Bayesian formalism; classification; conditional probability; content; content-based retrieval; image database; index; optimal model complexity; remote sensing image; sub-band predictive models; texture characterization; texture segmentation; wavelet coefficient; Bayesian methods; Content based retrieval; Image databases; Image retrieval; Image segmentation; Indexes; Information retrieval; Predictive models; Remote sensing; Wavelet coefficients;
Conference_Titel :
Geoscience and Remote Sensing Symposium, 1999. IGARSS '99 Proceedings. IEEE 1999 International
Conference_Location :
Hamburg
Print_ISBN :
0-7803-5207-6
DOI :
10.1109/IGARSS.1999.773492
