Introduction to information theory and data compression pdf
ECE/ Data Compression and Information TheoryIn computer science and information theory, data compression or source coding is the process of encoding information using fewer bits than an unencoded representation would use, through use of specific encoding schemes. As with any communication, compressed data communication only works when both the sender and receiver of the information understand the encoding scheme. For example, this text makes sense only if the receiver understands that it is intended to be interpreted as characters representing theEnglish language. Similarly, compressed data can only be understood if the decoding method is known by the receiver. Compression is useful because it helps reduce the consumption of expensive resources, such as hard disk space or transmission bandwidth. On the downside, compressed data must be decompressed to be used, and this extra processing may be detrimental to some applications. For instance, a compression scheme for video may require expensive hardware for the video to be decompressed fast enough to be viewed as its being decompressed the option of decompressing the video in full before watching it may be inconvenient, and requires storage space for the decompressed video.
Lecture 2: Entropy and Data Compression (I): Introduction to Compression, contractorprofitzone.com and Entropy
Implementation of Lempel-ZIV algorithm for lossless compression using VHDL
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