Information Extraction from High Resolution Satellite Imagery Using Integration Technique

This paper presents an integration technique for extraction of Information from high resolution satellite image and also demonstrates the accuracy achieved by the final extracted information. The integration technique comprises of an improved mathematical morphology based watershed transform and a non-linear derivative method. It overcomes all the disadvantages of existing region based and edge based methods by incorporating aforesaid integration methods. It preserves the advantages of multi-resolution and multi-scale gradient approaches. Using these approaches, it avoids excessive fragmentation into regions. The watershed segmentation is proved to be a powerful and fast technique for both contour detection and region-based segmentation. In principle, watershed segmentation depends on ridges to perform a proper segmentation, a property that is often fulfilled for contour detection where the boundaries of the objects have been expressed as ridges. On the other hand, the non-linear 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. This nonlinearity will effectively improve global filtration process and regarded to be an effective technique for regularization in order to provide information extraction in a valid manner. The practical merit of this proposed method is to derive an impervious surface from emerging urban areas. Hence this proposed method gives a major contribution in the field of satellite image for information extraction.