A survey on data compression techniques: From the perspective of data quality, coding schemes, data type and applications
Author(s) -
J. Uthayakumar,
T. Vengattaraman,
P. Dhavachelvan
Publication year - 2018
Publication title -
journal of king saud university - computer and information sciences
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.617
H-Index - 33
eISSN - 2213-1248
pISSN - 1319-1578
DOI - 10.1016/j.jksuci.2018.05.006
Subject(s) - computer science , data quality , data compression , data type , coding (social sciences) , computer data storage , data science , data mining , engineering , computer hardware , artificial intelligence , operations management , metric (unit) , statistics , programming language , mathematics
Explosive growth of data in digital world leads to the requirement of efficient technique to store and transmit data. Due to limited resources, data compression (DC) techniques are proposed to minimize the size of data being stored or communicated. As DC concepts results to effective utilization of available storage area and communication bandwidth, numerous approaches were developed in several aspects. In order to analyze how DC techniques and its applications have evolved, a detailed survey on many existing DC techniques is carried out to address the current requirements in terms of data quality, coding schemes, type of data and applications. A comparative analysis is also performed to identify the contribution of reviewed techniques in terms of their characteristics, underlying concepts, experimental factors and limitations. Finally, this paper insight to various open issues and research directions to explore the promising areas for future developments.
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