114 research outputs found

    Side-information generation for temporally and spatially scalablewyner-ziv codecs

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    The distributed video coding paradigmenables video codecs to operate with reversed complexity, in which the complexity is shifted from the encoder toward the decoder. Its performance is heavily dependent on the quality of the side information generated by motio estimation at the decoder. We compare the rate-distortion performance of different side-information estimators, for both temporally and spatially scalableWyner-Ziv codecs. For the temporally scalable codec we compared an established method with a new algorithm that uses a linear-motion model to produce side-information. As a continuation of previous works, in this paper, we propose to use a super-resolution method to upsample the nonkey frame, for the spatial scalable codec, using the key frames as reference.We verify the performance of the spatial scalableWZcoding using the state-of-the-art video coding standard H.264/AVC

    GReEn: a tool for efficient compression of genome resequencing data

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    Research in the genomic sciences is confronted with the volume of sequencing and resequencing data increasing at a higher pace than that of data storage and communication resources, shifting a significant part of research budgets from the sequencing component of a project to the computational one. Hence, being able to efficiently store sequencing and resequencing data is a problem of paramount importance. In this article, we describe GReEn (Genome Resequencing Encoding), a tool for compressing genome resequencing data using a reference genome sequence. It overcomes some drawbacks of the recently proposed tool GRS, namely, the possibility of compressing sequences that cannot be handled by GRS, faster running times and compression gains of over 100-fold for some sequences. This tool is freely available for non-commercial use at ftp://ftp.ieeta.pt/∼ap/codecs/GReEn1.tar.gz

    Improved Sequential MAP estimation of CABAC encoded data with objective adjustment of the complexity/efficiency tradeoff

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    International audienceThis paper presents an efficient MAP estimator for the joint source-channel decoding of data encoded with a context adaptive binary arithmetic coder (CABAC). The decoding process is compatible with realistic implementations of CABAC in standards like H.264, i.e., handling adaptive probabilities, context modeling and integer arithmetic coding. Soft decoding is obtained using an improved sequential decoding technique, which allows to obtain various tradeoffs between complexity and efficiency. The algorithms are simulated in a context reminiscent of H264. Error detection is realized by exploiting on one side the properties of the binarization scheme and on the other side the redundancy left in the code string. As a result, the CABAC compression efficiency is preserved and no additional redundancy is introduced in the bit stream. Simulation results outline the efficiency of the proposed techniques for encoded data sent over AWGN and UMTS-OFDM channels

    Compressing Proteomes: The Relevance of Medium Range Correlations

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    We study the nonrandomness of proteome sequences by analysing the correlations that arise between amino acids at a short and medium range, more specifically, between amino acids located 10 or 100 residues apart; respectively. We show that statistical models that consider these two types of correlation are more likely to seize the information contained in protein sequences and thus achieve good compression rates. Finally, we propose that the cause for this redundancy is related to the evolutionary origin of proteomes and protein sequences

    An Adaptive Source-Channel Coding with Feedback for Progressive Transmission of Medical Images

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    A novel adaptive source-channel coding with feedback for progressive transmission of medical images is proposed here. In the source coding part, the transmission starts from the region of interest (RoI). The parity length in the channel code varies with respect to both the proximity of the image subblock to the RoI and the channel noise, which is iteratively estimated in the receiver. The overall transmitted data can be controlled by the user (clinician). In the case of medical data transmission, it is vital to keep the distortion level under control as in most of the cases certain clinically important regions have to be transmitted without any visible error. The proposed system significantly reduces the transmission time and error. Moreover, the system is very user friendly since the selection of the RoI, its size, overall code rate, and a number of test features such as noise level can be set by the users in both ends. A MATLAB-based TCP/IP connection has been established to demonstrate the proposed interactive and adaptive progressive transmission system. The proposed system is simulated for both binary symmetric channel (BSC) and Rayleigh channel. The experimental results verify the effectiveness of the design
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