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