Object-Level Highlight Features For High-resolutionSAR Building Extraction

Objective With the improvement of SAR image resolution,it is now increasingly used as an effectivedata support for building extraction.However,the traditional pixel-based method is not practicable inbuilding extraction.Not only are the result not amiable,but also the accuracy is very poor.So in thispaper we will firstly apply FNEA algorithm(fractal net evolution approach)on SAR image to obtainanalysis units.Then contextual feature of those object-level units will be utilized to propose the con-ception of highlight adjacent intensity(HAL)and shining point distribute density(SDD).After thatthese two features will be combined to be used in the process of object-level building extraction.Final-ly,a couple of experiments are conducted show that an object-oriented method outperforms pixel-based methods in building extraction from high-resolution SAR images.