Information Mining from Remote Sensing Imagery Based on Multi-scale and Multi-feature Processing Techniques

The paper attempts to present an information extraction approach in terms of image segmentation based on an object-oriented algorithm for high-resolution remote sensing images. The hierarchy frame and multi-features of the remote sensing image understanding and processing method are put forward. Firstly we extract various internal features of relatively homogeneous primitive objects using an image segmentation algorithm based on both spectral and shape information. Secondly, those primitives are analyzed to ascertain an optimal object by adopting certain feature rules, such as the traditional feature of the spectrum, shape, texture, spatial relation etc. Results from this research indicate that the model is practical to realize and the extraction accuracy of the coastal information is significantly improved compared to traditional approaches. Therefore, this study provides a potential way to serve our highly dynamic coastal zones for monitoring, management, development and utilization. * Corresponding author: Xaiomei Yang, E-mail: [email protected].