PhD defense : Shadow/Vegetation and Building detection from single optical remote sensing image

PhD defense : Tran-Thanh NGO

Team : MIV

Title : Shadow/Vegetation and Building detection from single optical remote sensing image

Abstract : This PhD thesis is devoted to the detection of shadows, vegetation and buildings from single high resolution optical remote sensing images. The first part introduces a new method for simultaneously detecting shadows and vegetation. Several shadow and vegetation indices were investigated and merged using the Dempster-Shafer evidence theory so as to obtain a segmentation map with three classes : “shadow”, “vegetation” and “other”. However, the performance of the fusion is sensitive to noise since it processes at a pixel-level. A Markov random field (MRF) is thus integrated to model spatial information within the image. In the second part, a novel region growing segmentation technique is proposed. The image is oversegmented into smaller homogeneous regions which replace the rigid structure of the pixel grid. An iterative region classification-merging is then applied over these regions. At each iteration, regions are classified using a MRF-based image segmentation, then, according to the position of shadows, regions having the same class are merged to produce shapes appropriate to rectangles. The final buildings are estimated using the recursive minimum bounding rectangle method from the final classification. These two algorithms have been validated on a variety of image datasets and demonstrate their efficiency.

This thesis was supervised by Christophe Collet and co-diriged by Vincent Mazet (University of Strasbourg).

The presentation will take place on Tuesday 22th September 2015 at 2.00pm in room A207 of the pôle API building in Illkirch.