The goal of data compression is to represent an information
source (e.g. a data file, a speech signal, an image, or a video signal) as accurately as possible using the fewest number of bits.
Theory of Data Compression:
This page includes an overview of the theory, source modeling
(including a statistical study of English text),
entropy rate, Shannon lossless source coding theorem, rate-distortion
theory, a discussion of the gap between theory and practice, and
Blahut algorithm. A list of recommended
books on data-compression
theory and some seminal papers (e.g., Shannon's 1948 paper A Mathematical
Theory of Communications) are also included.
Lossless Data Compression:
- Description of Huffman coding
and Lempel-Ziv coding (including an animation of the Huffman design
algorithm and an animation of the Lempel-Ziv
encoding). A performance comparison is also included.
- Description of the Linde Buzo Gray vector quantizer (VQ) design algorithm. Includes a two-dimensional animation
of the LBG-VQ design algorithm.
- Description of the LPC model, LPC vocoder, CELP coder, and ADPCM
coder. A comparison of these coders and references are also included.
- A demonstration of JPEG/JPEG2000 compression of color and gray-scaled images.
- Key papers on data compression and various source code (e.g., vector quantizer
design using the LBG algorithm) are available.
- Links to web sites relating to data compression. You many
add your link if you wish.