Advances in Visual Data Compression and Communication: by Feng Wu PDF

Imaging Systems

By Feng Wu

ISBN-10: 1482234157

ISBN-13: 9781482234152

Visible details is likely one of the richest and so much bandwidth-consuming modes of conversation. to fulfill the necessities of rising functions, strong information compression and transmission strategies are required to accomplish hugely effective communique, even within the presence of growing to be conversation channels that supply elevated bandwidth.

Presenting the result of the author’s years of study on visible information compression and transmission, Advances in visible facts Compression and verbal exchange: assembly the necessities of latest purposes offers a theoretical and technical foundation for complicated study on visible facts compression and communication.

The e-book stories the drifting challenge in scalable video coding, analyzes the explanations inflicting the matter, and proposes numerous strategies to the matter. It explores the author’s Barbell-based lifting coding scheme that has been followed as universal software program by means of MPEG. It additionally proposes a unified framework for deriving a directional rework from the nondirectional counterpart. The constitution of the framework and the statistic distribution of coefficients are just like these of the nondirectional transforms, which allows next entropy coding.

Exploring the visible correlation that exists in media, the textual content extends the present coding framework from diverse facets, together with complicated snapshot synthesis—from description and reconstruction to organizing correlated photographs as a pseudo series. It explains the right way to follow compressive sensing to resolve the information compression challenge in the course of transmission and covers novel study on compressive sensor info accumulating, random projection codes, and compressive modulation.

For analog and electronic transmission applied sciences, the ebook develops the pseudo-analog transmission for media and explores state of the art learn on allotted pseudo-analog transmission, denoising in pseudo-analog transmission, and aiding MIMO. It concludes by way of contemplating rising advancements of knowledge idea for destiny functions.

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Additional info for Advances in Visual Data Compression and Communication: Meeting the Requirements of New Applications

Example text

All random variables have the same distribution p(s). Furthermore, for any i = j, Si is independent of S j . ) source. In information theory, the analog of the law of large numbers is the asymptotic equipartition property (AEP). d. 12) in probability. It is a direct consequence of the weak law of large numbers. d. variables, 1/n ∑i Si is close to its expected value E(S) for large n. The AEP states that −1/n log p(S1 , S2 , · · · , Sn ) is close to the entropy H(S), where p(S1 , S2 , · · · , Sn ) is the probability of observing the sequence S1 , S2 , · · · , Sn .

26) only considers one random variable. Therefore, the rate distortion limit R(D) should be achieved by considering long block lengths. 1, after source coding, coded source X no longer contains any redundancy. If X is a k-dimensional bit vector, the space 2k will be fully occupied. Every value represents a valid message. It is very sensitive to channel noise because any corrupted bit in x will change x to another valid message. In this case, it is difficult to tell which x is really sent out. Therefore, in channel coding X is mapped into some sequence Y of channel codewords.

Therefore, it is desirable to have an efficient coding procedure that works for a long block of source letters. Huffman coding is not ideal for this situation, since it is a bottom-up procedure that requires the calculation of the probabilities of all source sequences of a particular block length and the construction of the corresponding complete code tree. Thus the block length is limited. A better scheme is one which can be easily extended to longer block lengths without having to redo all the calculations.

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Advances in Visual Data Compression and Communication: Meeting the Requirements of New Applications by Feng Wu


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