Tài liệu 55 Video Sequence Compression doc

Osama Al-Shaykh, et. Al. “Video Sequence Compression.”

2000 CRC Press LLC. <http://www.engnetbase.com>.

Video Sequence Compression

Osama Al-Shaykh

University of California,

Berkeley

Ralph Neff

University of California,

Berkeley

David Taubman

Hewlett Packard

Avideh Zakhor

University of California,

Berkeley

55.1 Introduction

55.2 Motion Compensated Video Coding

Motion Estimation and Compensation • Transformations •

Discussion • Quantization • Coding of Quantized Symbols

55.3 Desirable Features

Scalability • Error Resilience

55.4 Standards

H.261 • MPEG-1 • MPEG-2 • H.263 • MPEG-4

Acknowledgment

References

The image and video processing literature is rich with video compression algorithms.

This chapter overviews the basic blocks of most video compression systems, discusses

some important features required by many applications, e.g., scalability and error re￾silience, and reviews the existing video compression standards such as H.261, H.263,

MPEG-1, MPEG-2, and MPEG-4.

55.1 Introduction

Video sources produce data at very high bit rates. In many applications, the available bandwidth is

usually very limited. For example, the bit rate produced by a 30 frame/s color common intermediate

format (CIF) (352 × 288) video source is 73 Mbits/s. In order to transmit such a sequence over a

64 Kbits/s channel (e.g., ISDN line), we need to compress the video sequence by a factor of 1140. A

simple approach is to subsample the sequence in time and space. For example, if we subsample both

chroma components by 2 in each dimension, i.e., 4:2:0 format, and the whole sequence temporally

by 4, the bit rate becomes 9.1 Mbits/s. However, to transmit the video over a 64 kbits/s channel, it

is necessary to compress the subsampled sequence by another factor of 143. To achieve such high

compression ratios, we must tolerate some distortion in the subsampled frames.

Compression can be either lossless (reversible) or lossy (irreversible). A compression algorithm is

lossless if the signal can be reconstructed from the compressed information; otherwise it is lossy. The

compression performance of any lossy algorithm is usually described in terms of its rate-distortion

curve, which represents the potential trade-off between the bitrate and the distortion associated with

the lossy representation. The primary goal of any lossy compression algorithm is to optimize the

rate-distortion curve over some range of rates or levels of distortion. For video applications, rate

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