Interactive object segmentation in high resolution satellite images

High resolution remote sensing image segmentation is a great challenge in terms of potential applications, but also because of the difficulty of the task. Fully automatic algorithms are not able to extract all the desired features from complex images but visual image analysis is time consuming and tedious (therefore error prone). In this work we present a simple, yet powerful approach for interactive image segmentation. This approach combines the best of the automatic image processing together with the ability of a human operator to choose the objects of interest for a given application. Results are presented on a wide variety of objects and contexts.