A HYBRID APPROACH FOR INFORMATION EXTRACTION FROM HIGH RESOLUTION SATELLITE IMAGERY

Abstract

This paper presents a hybrid approach for extraction of information from high resolution satellite imagery and also demonstrates the accuracy achieved by the final extracted information. The hybrid technique comprises of improved marker-controlled watershed transforms and a nonlinear derivative method. It overcomes all the disadvantages of existing region-based and edge-based methods by incorporating aforesaid hybrid methods. It preserves the advantages of multi-resolution and multi-scale gradient approaches. Region-based segmentation also incorporates the watershed technique due to its better efficiency in segmentation. In principle, a proper segmentation can be performed perfectly by watershed technique on incorporating ridges. These ridges express as the object's boundaries according to the property of contour detection. On the other hand, the nonlinear derivative method is used for resolving the discrete edge detection problem. Since it automatically selects the best edge localization, which is very much useful for estimation of gradient selection. The main benefit of univocal edge localization is to provide a better direction estimation of the gradient, which helps in producing a confident edge reference map for synthetic images. The practical merit of this proposed method is to derive an impervious surface from emerging urban areas.