DocumentCode :
3690120
Title :
Pointwise approach on covariance matrix of oriented gradients for very high resolution image texture segmentation
Author :
Minh-Tan Pham;Grégoire Mercier;Julien Michel
Author_Institution :
TELECOM Bretagne - UMR CNRS 6285 Lab-STICC/CID
fYear :
2015
fDate :
7/1/2015 12:00:00 AM
Firstpage :
1008
Lastpage :
1011
Abstract :
The present study involves an investigation of a pointwise approach on the feature covariance matrix to extract textu-ral features for very high resolution (VHR) satellite images. Indeed, our proposition is to construct the covariance matrix of oriented gradients using a non-dense approach based on characteristic points extracted from the image. This novel non-dense covariance descriptor is capable of not only capturing both radiometric and local geometric information from the image, but also encoding their joint distribution and correlation, which are effectively relevant for texture characterization and discrimination. In order to demonstrate the efficiency of the proposed descriptor, a texture-based image segmentation stage is carried out. First efforts on VHR panchromatic images using the proposed algorithm provide very promising and competitive results compared to classical methods.
Keywords :
"Covariance matrices","Image segmentation","Feature extraction","Image resolution","Visualization","Measurement","Histograms"
Publisher :
ieee
Conference_Titel :
Geoscience and Remote Sensing Symposium (IGARSS), 2015 IEEE International
ISSN :
2153-6996
Electronic_ISBN :
2153-7003
Type :
conf
DOI :
10.1109/IGARSS.2015.7325939
Filename :
7325939
Link To Document :
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