A Review of Modern Paradigms in Data Compression Techniques
Giridhar S. Sudi, Meghana S. Kulkarni, Vikrant K. Shende · International Journal of Engineering Research in Electronics and Communication Engineering · 2015
Data compression has been extensively applied to the motion-picture industry and consumer electronics especially in high-definition TVs, advanced multi-media systems, remote sensing systems via satellite, aircraft, radar, teleconferencing, email and social media, mobile phones, hand held PCs etc. Efficient compression of data would significantly decrease the overheads in both the communication and data storage. The efficiency of a data compression scheme is measured by the compression ratio, the resulting distortion after lossy compression, and the implementation complexity. This paper reviews the evolution of compression techniques over the years and the present day modern techniques being explored. Artificial Intelligence (AI) approaches appear to be very promising for intelligent information processing due to their massively paralleled computing structures. The main problems solved by Artificial Intelligence (AI) techniques such as Artificial Neural Networks, Fuzzy Logic systems and Genetic Algorithms include optimization, classification, prediction and pattern recognition. Due to the efficiency of AI paradigms in solving complex problems, researchers are applying these techniques to develop new intelligent data compression systems. Keywards: Compression, compression ratio, Artificial Intelligence, Artificial Neural Network, Fuzzy Logic, Genetic Algorithms.