Vectorization of Large Amounts of Raster Satellite Images in a Distributed Architecture Using HIPI

Vectorization processes focus on grouping pixels of a raster image into raw line segments, and forming lines, polylines or polygons. To vectorize massive raster images regarding resource and performance problems, we use a distributed HIPI image processing interface based on MapReduce approach. Apache Hadoop is placed at the core of the framework. To realize such a system, we first define mapper function, and then its input and output formats. In this paper, mappers convert raster mosaics into vector counterparts. Reducer functions are not needed for vectorization. Vector representations of the raster images is expected to give better performance in distributed computations by reducing the negative effects of bandwidth problem and horizontal scalability analysis is done.