Watershed Segmentation of High-Resolution Remotely Sensed Imagery

High-resolution remotely sensed data such as SPOT-5 imagery are employed to study the effectiveness of the watershed segmentation algorithm. Existing problems in this approach are identified and appropriate solutions are proposed. As a case study, the panchromatic SPOT-5 image of part of Beijing urban areas has been segmented by using the MATLAB software. In segmentation, the structuring element has been firstly created, then the gaps between objects have been exaggerated and the objects of interest are converted. After that, the intensity valleys have been detected and the watershed segmentation have been conducted. Through this process, the objects in an image are divided into separate objects. Finally, the effectiveness of the watershed segmentation approach for high-resolution imagery has been summarized. The approach to solve the problems such as over-segmentation has been proposed.