A multi-spectral texture characterisation model is proposed, the Multi-spectral Local Differences Texem – 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.
|Translated title of the contribution||Multi-spectral Texture Characterisation for Remote Sensing Image Segmentation|
|Journal||Proceedings of the 4th Iberian Pattern Recognition and Image Analysis Conference|
|Publication status||Published - 2009|
Bibliographical noteISBN: 9783642021718
Publisher: Springer, Lecture Notes in Computer Science
Name and Venue of Conference: Proceedings of the 4th Iberian Pattern Recognition and Image Analysis Conference
Other identifier: 2000999