By Wu F.
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Extra resources for Advances in visual data compression and communication
The combination will be as efficient as anything we could design by considering both problems together. This offers an enormous reduction in complexity. Therefore, in practical applications, source coding and channel coding are often studied separately. However, it may be appropriate to point out that this is not always true. There are examples of multiuser channels where decomposition breaks down. Another simple example is that of sending English text over an erasure channel. We can look for the most efficient binary representation of the text and send it over the channel.
Assume the one stage coding is considered. We map the sequence onto a codeword Y n (Sn ) and send the codeword over the channel. The receiver looks at his received sequence Yˆ n and makes an estimation Sˆn of the sequence Sn that was sent. The receiver makes an error if (n) Sˆn 6= Sn . 66) yˆn sn where I is the indicator function and g(yˆn ) is the decoding function. 4. If S1 , S2 , , Sn is a nite alphabet stochastic process that satis es the (n) AEP, then there exists a source channel code with Pe !
This format is called interlaced video. Two successive fields can be combined to a picture. To support the properties of interlaced video, MPEG-2 specifies different methods for field/picture adaptive motion compensation (picture based, field based, and dual prime prediction modes), as well as switching between field/picture-wise DCT. Further, it is possible to switch into a 16 × 8 prediction mode, where separate motion vectors can be defined for the top and bottom halves of a MB. MPEG-2 is the first standard to support scalable video coding (SVC), which provides signal-to-noise ratio (SNR) scalability and spatial scalability over a limited number of layers.
Advances in visual data compression and communication by Wu F.