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Analysis and comparison of various compression methods used for storing massive geodata objects

Publisher : ICCIDS 2017 - International Conference on Computational Intelligence in Data Science, Proceedings

Campus : Bengaluru

School : School of Engineering

Department : Computer Science

Year : 2018

Abstract : Massive geodata is generally defined by its storage requirements and not by objects' geographic extent. It should be optimized to improve time and space complexity which can be achieved via compression. The methodologies used in image compression applications are classified as lossy and lossless compression. Image compression applications compress images which in turn lead to efficient utilization of time, memory and bandwidth. In this paper, various compression methods for massive geodata objects have been analyzed and compared which will ultimately help in identifying optimal compression method as per different requirements or depending on specific type of geodata. Algorithms have been compared based on efficiency, compression ratio, PSNR & error estimates. © 2017 IEEE.

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