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Multi-spectral Texture Characterisation for Remote Sensing Image Segmentation

Filiberto Pla, Gema Gracia, Pedro Garc?-a-Sevilla, Majid Mirmehdi, Xianghua Xie, Multi-spectral Texture Characterisation for Remote Sensing Image Segmentation. Proceedings of the 4th Iberian Pattern Recognition and Image Analysis Conference. ISBN 978-3-642-02171-8, pp. 257–264. June 2009. PDF, 462 Kbytes.

Abstract

A multi-spectral texture characterisation model is proposed, the Multi-spectral Local Differences Texem a?? MLDT, as an affordable approach to be used in multi-spectral images that contain large number of bands. The MLDT is based on the Texem model. Using an inter-scale post-fusion strategy for image segmentation, framed in a multi-resolution approach, we produce unsupervised multi-spectral image segmentations. Preliminary results on several remote sensing multi-spectral images exhibit a promising performance by the MLDT approach, with further improvements possible to model more complex textures and add some other features, like invariance to spectral intensity.

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