Aimed at solving the problem of teacher computer screen information transmission on the Internet and storage in the hard disk in the distance education, this paper analyzes the characteristic of screen capture and los...
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ISBN:
(纸本)9781424409723
Aimed at solving the problem of teacher computer screen information transmission on the Internet and storage in the hard disk in the distance education, this paper analyzes the characteristic of screen capture and lossless compression in the online teaching. It proposes a novel solution for screen capture based on content increment and arithmetic coding to produce screen stream and transmit simultaneously with teacher's audio/video streams on the Internet and make multimedia courseware in the hard disk at the same time. The effectiveness and good results of this method in real-time and non-real-time learning have been testified by the real system.
The commonly used data compression techniques do not necessarily provide maximal compression and neither do they define the most efficient framework for transmission of data. In this thesis we investigate variants of ...
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The commonly used data compression techniques do not necessarily provide maximal compression and neither do they define the most efficient framework for transmission of data. In this thesis we investigate variants of the standard compression algorithms that use the strategy of partitioning of the data to be compressed. Doing so not only increases the compression ratio in many instances, it also reduces the maximum data block size for transmission. The partitioning of the data is made using a Markov model to predict if doing so would result in increased compression ratio. Experiments have been performed on text files comparing the new scheme to adaptive Huffman and arithmetic coding methods. The adaptive Huffman method has been implemented in a new way by combining the FGK method with Vitter's implicit ordering of nodes.
Scalable to lossless (SLS) audio coding is a state-of-art audio coding technique that has been adopted as MPEG scalable audio coding tool. To realize bit-plane refinement, this technique employs bit-plane arithmetic c...
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ISBN:
(纸本)9781424442966
Scalable to lossless (SLS) audio coding is a state-of-art audio coding technique that has been adopted as MPEG scalable audio coding tool. To realize bit-plane refinement, this technique employs bit-plane arithmetic coding for lossless entropy coding, and Laplacian distribution is used to model the input data to realize high compression efficiency. In this paper, bit-plane probability is analyzed when generalized Gaussian distribution is used to model the input data. Based on the result of bit-plane probability for generalized Gaussian distribution, a low cost bit-plane arithmetic coding method is presented. This scheme is implemented in the SLS audio coding platform. With the same computational complexity, the proposed algorithm presents higher compression efficiency than SLS.
In this study an adaptive arithmetic coder is embedded in the Baptista-type chaotic cryptosystem for implementing secure data compression. To build the multiple lookup tables of secure data compression, the phase spac...
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In this study an adaptive arithmetic coder is embedded in the Baptista-type chaotic cryptosystem for implementing secure data compression. To build the multiple lookup tables of secure data compression, the phase space of chaos map with a uniform distribution in the search mode is divided non-uniformly according to the dynamic probability estimation of plaintext symbols. As a result, more probable symbols are selected according to the local statistical characters of plaintext and the required number of iterations is small since the more probable symbols have a higher chance to be visited by the chaotic search trajectory. By exploiting non-uniformity in the probabilities under which a number of iteration to be coded takes on its possible values, the compression capability is achieved by adaptive arithmetic code. Therefore, the system offers both compression and security. Compared with original arithmetic coding, simulation results on Calgary Corpus files show that the proposed scheme suffers from a reduction in compression performance less than 12% and is not susceptible to previously carried out attacks on arithmetic coding algorithms.
We propose an algorithm for the hierarchical aggregation of observations in dissemination-based, distributed traffic information systems. Instead of transmitting observed parameters directly, we propose soft-state ske...
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We propose an algorithm for the hierarchical aggregation of observations in dissemination-based, distributed traffic information systems. Instead of transmitting observed parameters directly, we propose soft-state sketches an extension of Flajolet-Martin sketches as a probabilistic approximation. This data representation is duplicate insensitive, a trait that overcomes two central problems of existing aggregation schemes for VANET applications. First, when multiple aggregates of observations for the same area are available, it is possible to combine them into an aggregate containing all information from the original aggregates. This is fundamentally different from existing approaches where typically one of the aggregates is selected for further use while the rest is discarded. Second, any observation or aggregate can be included into higher-level aggregates, regardless if it has already been previously directly or indirectly added. Those characteristics result in a very flexible aggregate construction and a high quality of the aggregates. We demonstrate these traits of our approach by a simulation study. (c) 2010 Elsevier B.V. All rights reserved.
Scalable to lossless (SLS) audio coding is a state-of-art audio coding technique that has been adopted as MPEG scalable audio coding tool. To realize bit-plane refinement, this technique employs bit-plane arithmetic c...
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ISBN:
(纸本)9781424442959;9781424442966
Scalable to lossless (SLS) audio coding is a state-of-art audio coding technique that has been adopted as MPEG scalable audio coding tool. To realize bit-plane refinement, this technique employs bit-plane arithmetic coding for lossless entropy coding, and Laplacian distribution is used to model the input data to realize high compression efficiency. In this paper, bit-plane probability is analyzed when generalized Gaussian distribution is used to model the input data. Based on the result of bit-plane probability for generalized Gaussian distribution, a low cost bit-plane arithmetic coding method is presented. This scheme is implemented in the SLS audio coding platform. With the same computational complexity, the proposed algorithm presents higher compression efficiency than SLS.
A coding algorithm for lossless compression of audio signals is presented. The proposed algorithm consists of a lossy coding part and a lossless coding part. The lossy coding part is based on code excitation approach ...
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A coding algorithm for lossless compression of audio signals is presented. The proposed algorithm consists of a lossy coding part and a lossless coding part. The lossy coding part is based on code excitation approach where the excitation gain and the short-term prediction coefficients are adapted in a sample-by-sample fashion to cope with rapid time-varying nature of audio signals. The error between the input and the code-excited synthetic signal is then encoded by an arithmetic coder to achieve lossless compression. The excitation codebook is searched by using an M-L tree search strategy with minimum error energy and minimum code length after arithmetic coding as search criteria. The proposed coder has very low decoding complexity due to its simple code excitation structure and achieves compression performance comparable to other advanced lossless coders for coding CD quality audio.
Inserting redundancy to arithmetic codes is a common strategy to add error detection capability to this well-known family of source codes. By using this strategy error correction is possible through some decoding algo...
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ISBN:
(纸本)9781424433544
Inserting redundancy to arithmetic codes is a common strategy to add error detection capability to this well-known family of source codes. By using this strategy error correction is possible through some decoding algorithms such as Viterbi decoder. In this paper a system has proposed that uses finite state integer arithmetic codes (FSAC) as a joint source-channel code in combination with a cyclic redundancy check (CRC) and a List Viterbi decoder. The proposed scheme has shown better performance than previous ones.
In this paper we propose applying an adaptive context tree weighting method with a forbidden symbol in the H.264 coder. arithmetic codes with a forbidden symbol and a trellis search techniques are employed on an order...
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ISBN:
(纸本)9781424409969
In this paper we propose applying an adaptive context tree weighting method with a forbidden symbol in the H.264 coder. arithmetic codes with a forbidden symbol and a trellis search techniques are employed on an order to estimate the best transmitted codeword. Instead of using the context modeling defined in the H.264 standard, the arithmetic code with a forbidden symbol uses a CTW method. The CABAC algorithm is replaced by GRASP algorithm and the experimental results show that coding gains similar or superior to those obtained with the H.264/AVC CABAC algorithm and arithmetic coding.
Past research in the field of cryptography has not given much consideration to arithmetic coding as a feasible encryption technique, with studies proving compression-specific arithmetic coding to be largely unsuitable...
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Past research in the field of cryptography has not given much consideration to arithmetic coding as a feasible encryption technique, with studies proving compression-specific arithmetic coding to be largely unsuitable for encryption. Nevertheless, adaptive modeling, which offers a huge model, variable in structure, and as completely as possible a function of the entire text that has been transmitted since the time the model was initialized, is a suitable candidate for a possible encryption-compression combine. The focus of the work presented in this paper has been to incorporate recent results of chaos theory, proven to be cryptographically secure, into arithmetic coding, to devise a convenient method to make the structure of the model unpredictable and variable in nature, and yet to retain, as far as is possible, statistical harmony, so that compression is possible. A chaos-based adaptive arithmetic coding-encryption technique has been designed, developed and tested and its implementation has been discussed. For typical text files, the proposed encoder gives compression between 67.5% and 70.5%, the zeroth-order compression suffering by about 6% due to encryption, and is not susceptible to previously carried out attacks on arithmetic coding algorithms.
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