Object-Oriented Method for Automatic Extraction of Road from High Resolution Satellite Images

As the information carried in a high spatial resolution image is not represented by single pixels but by meaningful image objects, which include the association of multiple pixels and their mutual relations, the object based method has become one of the most commonly used strategies for the processing of high resolution imagery. This processing comprises two fundamental and critical steps towards content analysis and image understanding i.e. image segmentation and classification. This paper proposes a robust object based segmentation algorithm using multi-resolution analysis technique and object based supervised image classification using modified cloud basis functions (CBFs) neural network algorithm to identify road features from high resolution satellite remotely sensed images.