Satellite Images Vectorization Based on Clustering and Interpolation Technique

Abstract

Dealing with satellites Images, interpretation, improvement and modification area important issues of researchers concerning, because of the great benefits derived from them. GIS on the other hand is making to build disaster planning, crisis management, and alarm systems effective decision. In this paper a method for digitization gray scale satellite image to a digital map will propose. The proposed method depends on slicing the image into multi-layer, and preprocessing steps such as noise removal and contrast adjustment then use approach K-mean clustering unsupervised Classification . At the last step; the edges of segments (objects) are interpolated for softening the sharp edges using cubic spline interpolation, and these parts will be rendered with desired color that gets from original image. Layers results could be considered as one map for roads, buildings, green zones, etc. more than one layer could be merged in new map and may append information on it. The produced digital map will be saved as SVG vector file format.