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

Autor:	Eken, Suleyman, Aydin, Eray, Sayar, Ahmet
Rok vydání:	2018
Předmět:	Computer Science - Distributed Parallel and Cluster Computing
Druh dokumentu:	Working Paper
DOI:	10.1109/IDAP.2017.8090237
Popis:	Vectorization process focus on grouping pixels of a raster image into raw line segments, and forming lines, polylines or poligons. To vectorize massive raster images regarding resource and performane problems, weuse 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. Reduc functions are not needed for vectorization. Vector representations of 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. Comment: In Turkish, Proceedings of International Artificial Intelligence and Data Processing Symposium (IDAP) 2017
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1809.00235 Zobrazit plný text záznamu View this record from Arxiv