Adaptive lossless data compression algorithms with new approaches and modeling techniques
Nasser Tadayon · 1998
In many applications involving storage and transmission of there is an explicit need for compression. The aim of data is to convert information to new representation in the most efficient way possible. The information can be in many forms, such as text, voice, images, videos, and any other types of which can be transmitted from one place to another or stored in one place. We have considered lossless compression techniques, where the can be reconstructed uniquely and identically in absence of channel noise. We have introduced improvements on the existing modeling techniques such as LZW and CTW and have also introduced some new modeling techniques, such as Switching algorithm, Difference modeling technique, and Grouping algorithm. All lossless compression algorithms use some kind of prediction technique to overcome the zero frequency problem. In this aspect, two new prediction techniques have been presented and explored.