We present a complete processing line to generate an object based description of optical remote sensing (RS) images. A segmentation algorithm is used to generate a partition of regions and simplify the volume of data. Results are still at the pixel level. Based on topology analyses, a dynamical algorithm is proposed to retrieve, extract the segmented regions and encode them in a tree structure which describes their topological relations (adjacencies, inclusions). The overall collected information constitutes a consistent and independent database, generated efficiently on standard workstation. Many applications are possible, such as content based image retrieval, image description and compression, object classification or image-object fusion. A scenario is presented to emphasize interest of the method in the case of 3D visualization enhancement: image-objects are integrated on elevation data (digital elevation models, DEM) in order to generate more realistic rendering.
Object and topology extraction from remote sensing images
2005-01-01
911223 byte
Conference paper
Electronic Resource
English
Object and Topology Extraction from Remote Sensing Images
British Library Conference Proceedings | 2005
|Ship object detection in remote sensing images using convolutional neural networks
British Library Online Contents | 2017
|