# Introduction to Data Compression, Fourth Edition (The Morgan Kaufmann Series in Multimedia Information and Systems)

## Khalid Sayood

Language: English

Pages: 768

ISBN: 0124157963

Format: PDF / Kindle (mobi) / ePub

Each edition of *Introduction to Data Compression* has widely been considered the best introduction and reference text on the art and science of data compression, and the fourth edition continues in this tradition. Data compression techniques and technology are ever-evolving with new applications in image, speech, text, audio, and video. The fourth edition includes all the cutting edge updates the reader will need during the work day and in class.

Khalid Sayood provides an extensive introduction to the theory underlying today’s compression techniques with detailed instruction for their applications using several examples to explain the concepts. Encompassing the entire field of data compression, *Introduction to Data Compression* includes lossless and lossy compression, Huffman coding, arithmetic coding, dictionary techniques, context based compression, scalar and vector quantization. Khalid Sayood provides a working knowledge of data compression, giving the reader the tools to develop a complete and concise compression package upon completion of his book.

- New content added to include a more detailed description of the JPEG 2000 standard
- New content includes speech coding for internet applications
- Explains established and emerging standards in depth including JPEG 2000, JPEG-LS, MPEG-2, H.264, JBIG 2, ADPCM, LPC, CELP, MELP, and iLBC
- Source code provided via companion web site that gives readers the opportunity to build their own algorithms, choose and implement techniques in their own applications

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midrise quantizers. We will also generally assume that the input distribution is symmetric around the origin and the quantizer is also symmetric. (The optimal minimum mean squared error quantizer for a symmetric distribution need not be symmetric [120].) Given all these assumptions, the design of a uniform quantizer consists of finding the step size that minimizes the distortion for a given input process and number of decision levels. Uniform Quantization of a Uniformly Distributed Source

(76), we get and If the upper limit of the sum is infinity, we take the limit as goes to infinity. This limit exists only when . Using this formula, we get the Z-transform of the sequence as (78) (79) ♦ In this example the region of convergence is the region . For the Fourier transform to exist, we need to include the unit circle in the region of convergence. In order for this to happen, has to be less than one. Using this example, we can get some other Z-transforms that will be

pages 15–21, December 1983. 169. C.C. Cutler. Differential Quantization for Television Signals. U.S. Patent 2 605 361, July 29, 1952. 197. Y. Shoham and A. Gersho. Efficient bit allocation for an arbitrary set of quantizers. IEEE Transactions on Acoustics, Speech, and Signal Processing, ASSP-36:1445–1453, September 1988. 198. Malvar HS. Signal Processing with Lapped Transforms. Norwood, MA: Artech House; 1992. 203. A. Crosier, D. Esteban, and C. Galand. Perfect channel splitting by use of

differences and then computing the sum of the absolute value of the differences. If we assume that the closest block in the previous frame is located within 20 pixels in either the horizontal or vertical direction of the block to be encoded, we need to perform 1681 comparisons. There are several ways we can reduce the total number of computations. One way is to increase the size of the block. Increasing the size of the block means more computations per comparison. However, it also means that we

See also MPEG-1 video standard; Video compression base bitstream, 655–656 dual prime motion compensation, 657–658 Grand Alliance HDTV Proposal, 658 layered approach, 656 motion-compensated prediction modes, 657 profile-level combinations, 657 profiles, 655–656 scanning pattern for DCT coefficients, 658 168 motion compensation, 657–658 MPEG-4 AAC, 586 BSAC, 587 LTP, 586 PNS, 586 TwinVQ, 586 MPEG-4 advanced video coding. See H.264 MPEG-4 Part 10. See H.264 MPEG-4 Part 2 669. See