Lec #2 - Data Compression 2019/2020

The last decade we have been witnessing a transformation—some call it a revolution—in the way we communicate, and the process is still under way. This transformation includes the ever-growing Internet; the explosive development of mobile communications; and the ever-increasing importance of video communication. Data compression is one of the enabling technologies for each of these aspects of the multimedia revolution.
Data compression addresses the problem of reducing the amount of data required to represent a digital file, so that it can be stored or transmitted so efficiently.
The principle of data compression is that, it compresses data by removing redundancy from the original data in the source file.
On the other hand, information theory tells us that the amount of information conveyed by an event relates to its probability of occurrence. An event that is less likely to occur is said to contain more information than an event that is more likely to occur. The amount of information of an event and its probability are thus opposite.
Amount of information probability compression probability
It is obvious that information theory is the base theory that data compression relies on.
The problem of representing the source alphabet symbols Si in term of another system of symbols (usually the binary system consisting of the two symbols 0 & 1) is the main topic of coding theory.
An optimum coding scheme will use more bits for the symbols that less likely to occur, and a fewer bits for the symbols that frequently occur.
“Compression is all about the most compact representation of data.”