Ramin Samadani, Debargha Mukherjee, Ramin Samadani et al. · 2008
A printed photograph is difficult to reuse because the digital information that generated the print may no longer be available. This paper describes a mechanism for approximating the original digital image by combining a scan of the printed photograph with small amounts of digital auxiliary information kept together with the print. The auxiliary information consists of a small amount of digital data to enable accurate registration and color-reproduction, followed by a larger amount of digital data to recover residual errors and lost frequencies by distributed Wyner-Ziv coding techniques. Approximating the original digital image enables many uses, including making good quality reprints from the original print, even when they are faded many years later. In essence, the print itself becomes the currency for archiving and repurposing digital images, without requiring computer infrastructure.
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Zixiang Xiong, A.D. Liveris, Yang Yang · 2010
This chapter contains sections titled: Introduction Theoretical Background Code Designs Applications Conclusions References
Cited by 2
Whang, Jay · TIB Data Manager · 2024
Cited by 0Open access
Z. Xiong, et al. · 2013
To motivate DSC, consider a wireless video sensor network consisting of clusters of low-cost video sensor nodes (VSNs), an aggregation node (AN) for each cluster, and a BS for surveillance applications. The lower tier VSNs are used for data acquisition and processing; the upper tier ANs are used for data fusion and transmitting information out of the network. This type of network is expected to operate unattended over an extended period of time. As such, VSN and AN power consumption cause severe system constraints; additionally, traditional, one-to-many, video processing that is routinely applied to sophisticated video encoders (e.g., MPEG compression) will not be suitable for use on a VSN. This is because under the traditional broadcast paradigm the video encoder is the computational workhorse
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Jay Whang, Alliot Nagle, Anish Acharya et al. · IEEE Journal on Selected Areas in Information Theory · 2024
We consider the Distributed Source Coding (DSC) problem concerning the task of encoding an input in the absence of correlated side information that is only available to the decoder. Remarkably, Slepian and Wolf showed in 1973 that an encoder without access to the side information can asymptotically achieve the same compression rate as when the side information is available to it. This seminal result was later extended to lossy compression of distributed sources by Wyner, Ziv, Berger, and Tung. While there is vast prior work on this topic, practical DSC has been limited to synthetic datasets and specific correlation structures. Here we present a framework for lossy DSC that is agnostic to the correlation structure and can scale to high dimensions. Rather than relying on hand-crafted source modeling, our method utilizes a conditional Vector-Quantized Variational auto-encoder (VQ-VAE) to learn the distributed encoder and decoder. We evaluate our method on multiple datasets and show that our method can handle complex correlations and achieves state-of-the-art PSNR.
Cited by 10
Raymond W. Yeung, Zhen Zhang · 2002
Inspired by mobile satellite communication systems, we consider a source coding system which consists of multiple sources, multiple encoders, and multiple decoders. Each encoder has access to a certain subset of the sources, each decoder has access to a certain subset of the encoders, and each decoder reconstructs a certain subset of the sources almost perfectly. The connectivity between the sources and the encoders, the connectivity between the encoders and the decoders, and the reconstruction requirements for the decoders are all arbitrary. We obtain inner and outer bounds of the coding rate region in terms of /spl Gamma/* and /spl Gamma/*, respectively, which are fundamental regions in the entropy space defined by Yeung.
Cited by 3
David Varodayan, Yao-Chung Lin, Bernd Girod · IEEE Transactions on Image Processing · 2011
We consider distributed source coding in the presence of hidden variables that parameterize the statistical dependence among sources. We derive the Slepian-Wolf bound and devise coding algorithms for a block-candidate model of this problem. The encoder sends, in addition to syndrome bits, a portion of the source to the decoder uncoded as doping bits. The decoder uses the sum-product algorithm to simultaneously recover the source symbols and the hidden statistical dependence variables. We also develop novel techniques based on density evolution (DE) to analyze the coding algorithms. We experimentally confirm that our DE analysis closely approximates practical performance. This result allows us to efficiently optimize parameters of the algorithms. In particular, we show that the system performs close to the Slepian-Wolf bound when an appropriate doping rate is selected. We then apply our coding and analysis techniques to a reduced-reference video quality monitoring system and show a bit rate saving of about 75% compared with fixed-length coding.
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Franck Guo, David Rebollo-monedero · 2002
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Vinod M. Prabhakaran, Kannan Ramchandran · 2007
Exploiting correlated observations at multiple remote nodes for generating a secret common randomness to facilitate secure communication of data between the terminals has been addressed by many authors [1][2][3]. But in many applications such as sensor networks, the correlated observations might themselves be the data that need to be communicated. We address this problem of secure distributed source coding where we want to leak the least amount of information about the sources to an eavesdropper who may have access to a correlated observation of its own and who can listen in on the communication between the distributed encoders. The focus here is on minimizing the amount of information revealed to the eavesdropper rather than on minimizing the rate required to effect the communication.
Cited by 78
Haishan Wang · 2011
L'auteur a accorde une licence non exclusive permettant a la Bibliotheque et Archives Canada de reproduire, publier, archiver, sauvegarder, conserver, transmettre au public par telecommunication ou par I'lnternet, preter, distribuer et vendre des theses partout dans le monde, a des fins commerciales ou autres, sur support microforme, papier, electronique et/ou autres formats.
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Maria Fresia, Luc Vandendorpe · 2007
In this paper the problem of distributed source coding (DSC) of binary sources with side information at the decoder is addressed. We propose a scheme based on Raptor codes which are a new class of rateless codes. We adapt the decoding scheme to this problem by implementing the message passing strategy between the constituent decoders of Raptor codes at each decoding iteration. The proposed approach enables to achieve better performances than those achieved by the solutions based on turbo codes, and by the solutions based on regular low density parity check codes (LDPC) codes.
Cited by 13
Saygun Önay · Electronics Letters · 2013
A polar coding method to construct a distributed source coding scheme which can achieve any point on the dominant face of the Slepian‐Wolf rate region for sources with uniform marginals is proposed. Source encoding and decoding operations are performed using efficient algorithms which makes practical implementation feasible. Simulation results are given to exhibit the performance of the presented method.
Cited by 6Open access
Yao-Chung Lin, David Varodayan, Bernd Girod · IEEE Transactions on Image Processing · 2011
We present a novel approach using distributed source coding for image authentication. The key idea is to provide a Slepian-Wolf encoded quantized image projection as authentication data. This version can be correctly decoded with the help of an authentic image as side information. Distributed source coding provides the desired robustness against legitimate variations while detecting illegitimate modification. The decoder incorporating expectation maximization algorithms can authenticate images which have undergone contrast, brightness, and affine warping adjustments. Our authentication system also offers tampering localization by using the sum-product algorithm.
Cited by 36
Zixiang Xiong, Angelos D. Liveris, Samuel Cheng · 2004
n recent years, sensor research has been undergoing a quiet revolution, promising to have a significant impact throughout society that could quite possibly dwarf pre-vious milestones in the information revolution. MIT Technology Review ranked wireless sensor networks that con-sist of many tiny, low-power and cheap wireless sensors as the number one emerging technology. Unlike PCs or the Internet, which are designed to support all types of applications, sensor networks are usually mission driven and application specific (be it detection of biological agents and toxic chemicals; environmental measure-ment of temperature, pressure and vibration; or real-time area video surveillance). Thus they must operate under a set of unique constraints and requirements. For example, in contrast to many other wireless devices (e.g., cellular phones, PDAs, and laptops), in which energy can be recharged from time to time, the energy provisioned for a wireless sensor node is not expected to be renewed throughout its mission. The limited amount of energy available to wireless sensors has a significant impact on all aspects of a wireless sensor network, from the amount of information that the node can process, to the volume of wireless communication it can carry across large distances. Realizing the great promise of sensor networks requires more than a mere advance in individual technologies; it relies on many com-ponents working together in an efficient, unattended, comprehensible, and trustworthy manner. One of the enabling technologies for sensor networks is distributed source coding (DSC), which refers to the compression of multiple correlated sensor out-puts [1]–[4] that do not communicate with each other (hence distributed coding). These sensors send their compressed outputs to a central point [e.g., the base station (BS)] for joint decoding. I
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Mehrdad Teratani, Toshiaki Fujii, Masayuki Tanimoto · Dépôt institutionnel de l'Université libre de Bruxelles (Université Libre de Bruxelles) · 2002
info:eu-repo/semantics/published
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V. Toto-Zarasoa, Aline Roumy, Christine Guillemot · IEEE Transactions on Circuits and Systems for Video Technology · 2011
This paper studies source and correlation models for distributed video coding (DVC). It first considers a two-state HMM, i.e., a Gilbert-Elliott process, to model the bit-planes produced by DVC schemes. A statistical analysis shows that this model allows us to accurately capture the memory present in the video bit-planes. The achievable rate bounds are derived for these ergodic sources, first assuming an additive binary symmetric correlation channel between the two sources. These bounds show that a rate gain can be achieved by exploiting the sources memory with the additive BSC model. A Slepian-Wolf decoding algorithm which jointly estimates the sources and the source model parameters is then described. Simulation results show that the additive correlation model does not always fit well with the correlation between the actual video bit-planes. This has led us to consider a second correlation model (the predictive model). The rate bounds are then derived for the predictive correlation model in the case of memory sources, showing that exploiting the source memory does not bring any rate gain and that the noise statistic is a sufficient statistic for the MAP decoder. We also evaluate the rate loss when the correlation model assumed by the decoder is not matched to the true one. An a posteriori estimation of the correlation channel has hence been added to the decoder in order to use the most appropriate correlation model for each bit-plane. The new decoding algorithm has been integrated in a DVC decoder, leading to a rate saving of up to 10.14% for the same PSNR, with respect to the case where the bit-planes are assumed to be memoryless uniform sources correlated with the SI via an additive channel model.
Cited by 17
Aline Roumy, Christine Guillemot · 2006
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K. Mohan K. Mohan, P. Kumaran · Indian Journal Of Applied Research · 2011
IJAR - Indian Journal of Applied Research (IJAR) IJAR is a double reviewed monthly print journal that accepts research works from scholars, academicians, professors, doctorates, lecturers, and corporate in their respective expertise of studies.
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2008
Motion Compensated Temporal Filtering (MCTF) has proved to be an efficient coding tool in the design of open-loop scalable video codecs. In this paper we propose a MCTF video coding scheme based on lifting where the prediction step is implemented using PRISM (Power efficient, Robust, hIgh compression Syndromebased Multimedia coding), a video coding framework built on distributed source coding principles. We study the effect of integrating the update step at the encoder or at the decoder side. We show that the latter approach allows to improve the quality of the side information exploited during decoding. We present the analytical results obtained by modeling the video signal along the motion trajectories as an AR(1) process showing that the update step at the decoder allows to half the contribution of the quantization noise. We also include experimental results with real video data that demonstrate the potential of this approach when the video sequences are coded at low bitrates. 1.
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Çağatay Dikici, Radhouane Guermazi, Khalid Idrissi et al. · Zenodo (CERN European Organization for Nuclear Research) · 2005
Publication in the conference proceedings of EUSIPCO, Antalya, Turkey, 2005
Cited by 4Open access