By Feng Wu
Visible details is among the richest and so much bandwidth-consuming modes of verbal exchange. to satisfy the necessities of rising functions, robust info compression and transmission suggestions are required to accomplish hugely effective verbal exchange, even within the presence of becoming conversation channels that supply elevated bandwidth.Presenting the result of the author's years of study on visible data compression and transmission, Advances in visible info Compression and communique: assembly the necessities of recent functions presents a theoretical. Read more...
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Additional resources for Advances in Visual Data Compression and Communication: Meeting the Requirements of New Applications
In other words, using Hamming codes cannot approach the channel capacity. The capacity-approached channel codes will be discussed in Chapter 3. 3). Is the condition H < C necessary and sufficient for sending a source over a channel? For example, consider sending digital image or video over a discrete channel that is without memory. We could design a code to map the sequence of visual samples directly into the input of the channel, or we could compress the visual samples into its most efficient representation, then using the appropriate channel code to send it over the channel.
D. from a Gaussian distribution with variable σ 2 . Thus Yˆi = Yi + Zi , Zi ∼ N(0, σ 2 ). 46) The noise Zi is assumed to be independent of the signal Yi . Without further conditions, the capacity of this channel may be infinite. If the noise variance is zero, then the receiver receives the transmitted symbol perfectly. If the noise variance is nonzero and there is no constraint on the input, we can choose an infinite subset of inputs arbitrarily far apart, so that they are distinguishable at the output with an arbitrarily small probability of error.
Spatial redundancy — Neighboring pixels in a picture have similar values because the captured objects and background in a scene usually have some texture consistent regions. The strong correlation among pixels indicate that they can be efficiently represented in frequency domain. 3. Visual redundancy — Human visual system (HVS) is insensitive to a certain loss in visual data. It indicates that we can change visual data to some extent so that it can be compressed more efficiently. The distortion incurred by such information loss is often invisible to HVS.
Advances in Visual Data Compression and Communication: Meeting the Requirements of New Applications by Feng Wu