NDLI: Pointwise approach on covariance matrix of oriented gradients for very high resolution image texture segmentation

Content Provider	IEEE Xplore Digital Library
Author	Minh-Tan Pham Mercier, G. Michel, J.
Copyright Year	2015
Description	Author affiliation: Lab.-STICC/CID, TELECOM Bretagne, Brest, France (Minh-Tan Pham; Mercier, G.) \|\| DCT/SI/AP, CNES, Toulouse, France (Michel, J.)
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.
Starting Page	1008
Ending Page	1011
File Size	2075014
Page Count	4
File Format	PDF
e-ISBN	9781479979295
DOI	10.1109/IGARSS.2015.7325939
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2015-07-26
Publisher Place	Italy
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Covariance matrices Image segmentation Feature extraction Image resolution Visualization Measurement Histograms image segmentation Very high resolution images texture pointwise approach covariance matrix image gradients
Content Type	Text
Resource Type	Article

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