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distributed Lossless Compression Algorithm for Hyperspectral Images Based on Classification

SPECTROSCOPY LETTERS 2015年第7期48卷 528-535页

作者： Huang, Bingchao Nian, Yongjian Wan, Jianwei Natl Univ Def Technol Coll Elect Sci & Engn Changsha 410073 Hunan Peoples R China

This article addresses the problem of distributed lossless compression for hyperspectral images and proposes an effective lossless compression algorithm based on classification. First, a band selection algorithm was performed on the hyperspectral images to select those bands with considerable information. Next, the K-means algorithm was performed on those selected bands to obtain the classification map. To make full use of the spectral and spatial correlation, a multilinear regression model was introduced to construct the high-quality side information of each class within the identical block according to the classification map. Subsequently, the (n, k) linear grouping codes were employed to perform the distributed source coding for each class separately. The experimental results showed that the proposed algorithm has a competitive lossless compression performance compared with other state-of-the-art algorithms.

关键词： band selection distributed source coding hyperspectral images lossless compression spectral classification

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REDUNDANT FRAME STRUCTURE USING M-FRAME FOR INTERACTIVE LIGHT FIELD STREAMING

REDUNDANT FRAME STRUCTURE USING M-FRAME FOR INTERACTIVE LIGH...

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IEEE International Conference on Image Processing

作者： Benedicte Motz Gene Cheung Antonio Ortega The Graduate University for Advanced Studies National Institute of Informatics University of Southern California

ISBN: (纸本)9781467399623

A light field (LF) is a 2D array of closely spaced viewpoint images of a static 3D scene. In an interactive LF streaming (ILFS) scenario, a user successively requests desired neighboring viewpoints for observation, and in response the server must transmit pre-encoded data for correct decoding of the requested viewpoint images. Designing frame structures for ILFS is challenging, since at encoding time it is not known what navigation path a user will take, making differential coding very difficult to employ. In this paper, leveraging on a recent work on the merge operator - a new distributed source coding technique that efficiently merges differences among a set of side information (SI) frames into an identical reconstruction - we design redundant frame structures that facilitate ILFS, trading off expected transmission cost with total storage size. Specifically, we first propose a new view interaction model that captures view navigation tendencies of typical users. Assuming a flexible one-frame buffer at the decoder, we then derive a set of recursive equations that compute the expected transmission cost for a navigation lifetime of T views, given the proposed interaction model and a pre-encoded frame structure. Finally, we propose an algorithm that greedily builds a redundant frame structure, minimizing a weighted sum of expected transmission cost and total storage size. Experimental results show that our proposed algorithm generates frame structures with better transmission/storage tradeoffs than competing schemes.

关键词： Interactive streaming Light field distributed source coding

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Optimal Rate for Joint source-Channel coding of Correlated sources Over Orthogonal Channels

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IEEE COMMUNICATIONS LETTERS 2015年第1期19卷 22-25页

作者： Pujaico, Fernando Portugheis, Jaime Univ Estadual Campinas Dept Commun BR-13083852 Campinas SP Brazil Univ Estadual Campinas Sch Technol BR-13484332 Limeira SP Brazil

Joint source-channel coding of multiple correlated sources transmitted over orthogonal channels is considered. Two optimization problems related to coding schemes are formulated: maximal common rate, and maximal sum rate. These two problems model different power saving situations in energy-constrained wireless sensor networks. Solutions of these problems for an arbitrary number of sources are described, and some specific examples are given.

关键词： distributed source coding joint source-channel coding optimal rate

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Audio coding in wireless acoustic sensor networks

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SIGNAL PROCESSING 2015年 107卷 141-152页

作者： Zahedi, Adel Ostergaard, Jan Jensen, Soren Holdt Bech, Soren Naylor, Patrick Aalborg Univ Dept Elect Syst DK-9220 Aalborg Denmark Bang & Olufsen DK-7600 Struer Denmark Univ London Imperial Coll Sci Technol & Med Dept Elect & Elect Engn London SW7 2AZ England

In this paper, we consider the problem of source coding for a wireless acoustic sensor network where each node in the network makes its own noisy measurement of the sound field, and communicates with other nodes in the network by sending and receiving encoded versions of the measurements. To make use of the correlation between the sources available at the nodes, we consider the possibility of combining the measurement and the received messages into one single message at each node instead of forwarding the received messages and separate encoding of the measurement. Moreover, to exploit the correlation between the messages received by a node and the node's measurement of the source, we propose to use the measurement as side information and thereby form a distributed source coding (DSC) problem. Assuming that the sources are Gaussian, we then derive the rate-distortion function (RDF) for the resulting remote DSC problem under covariance matrix distortion constraints. We further show that for this problem, the Gaussian source is the worst to code. Thus, the Gaussian RDF provides an upper bound to other sources such as audio signals. We then turn our attention to audio signals. We consider an acoustical model based on the room impulse response (RIR) and provide simulation results for the rate-distortion performance in a practical setup where a set of microphones record the sound in a standard listening room. Since our reconstruction scheme and distortion measure are defined over the direct sound source, coding and dereverberation are performed in a joint manner. (C) 2014 Elsevier B.V. All rights reserved.

关键词： Wireless acoustic sensor network distributed source coding Rate-distortion function Covariance distortion constraint Zero-error coding

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A Centralized PSD Map Construction by distributed Compressive Sensing

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IEEE COMMUNICATIONS LETTERS 2015年第3期19卷 355-358页

作者： Eslami, Mohammad Torkamani-Azar, Farah Mehrshahi, Esfandiar Shahid Beheshti Univ GC Commun Engn Cognit Telecommun Res Grp Tehran *** Iran

In the context of spectrum reusing in Cognitive Radio (CR) networks, spectrum availability should be considered with respect to both space and frequency in making the Power Spectral Density (PSD) map concept. For this reason, the sensed PSDs by the distributed sensors in the area are collected and fused by a fusion center (FC). But, for a given zone, the sensed PSD by neighbor CR sensors may contain a shared common component for a while, and this component can be exploited in the theory of the distributed source coding to compress as much as possible. For this reason, distributed compressive sensing (DCS) methods are used here to exploit the correlation between PSDs and compress them more and reduce this type of overhead traffic. The proposed method can be used to develop a framework when the holding time of the users is large in comparison with the rate of the spectrum sensing.

关键词： Cognitive radio spectrum sensing PSD map compressive sensing distributed source coding joint sparsity model

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Joint distributed source and Network coding for Correlated Information Multicasting

Joint Distributed Source and Network Coding for Correlated I...

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International ICST Conference on Communications and Networking in China

作者： Shaoshuai Gao School of Information Science and Engineering Graduate University of Chinese Academy of Sciences

ISBN: (纸本)9781457701009

The problem of correlated information multicasting is considered in this paper, i.e., from multiple sources to multiple destinations through a network. It can be solved by jointly optimizing the distributed source coding and network coding. Previous research found that optimal performance can be achieved with unlimited decoding complexity, which cannot be applied in practical implementations. Some practical methods were also presented, which shows sub-optimal performance. To improve the coding performance and keep the low complexity of the algorithm, an adaptive coding and transmission scheme according to the conditional entropy of the sources is proposed. It has been demonstrated that the proposed scheme can achieve better performance compared with the existing ones.

关键词： distributed source coding Network coding Multicasting Sensor networks

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distributed source coding Using Raptor Codes for Hidden Markov sources

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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2009年第7期57卷 2868-2875页

作者： Fresia, M. Vandendorpe, L. Poor, H. V. Princeton Univ Dept Elect Engn Princeton NJ 08544 USA Catholic Univ Louvain Dept Elect Engn B-1348 Louvain Belgium

In this correspondence, the problem of distributed source coding (DSC) of binary sources with side information at the decoder is addressed. A scheme is proposed based on raptor codes which are a new class of rateless codes. The decoding scheme is adapted to this problem by implementing a message passing strategy between the constituent decoders of raptor codes at each decoding iteration. The case in which the sources are modeled as independent and identically distributed (i.i.d) processes as well as the more general case in which the sources are modeled as hidden Markov processes (HMPs) are considered. The proposed approach achieves better performance than those achieved by the solutions based on turbo codes, and by the solutions based on regular low density parity check (LDPC) codes when i.i.d. sources are considered. On the other hand, when modeling sources as HMPs, an additional module to exploit the underlying Markovian nature is necessary to achieve good performance.

关键词： distributed source coding Markov model raptor codes

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distributed Joint source-Channel coding Using Unequal Error Protection LDPC Codes

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IEEE TRANSACTIONS ON COMMUNICATIONS 2013年第8期61卷 3472-3482页

作者： Shahid, Iqbal Yahampath, Pradeepa Univ Manitoba Dept Elect & Comp Engn Winnipeg MB R3T 2N2 Canada

This paper presents a general approach to designing distributed joint source channel (DJSC) codes with arbitrary rates for communication of a pair of correlated binary sources over noisy channels. In this approach, both distributed compression and channel error correction are simultaneously achieved by transmitting, for each source, a fraction of the information bits together with the parity bits of a systematic channel code. This approach is shown to be asymptotically optimal, i.e., any rate-pair in the achievable rate-region can be approached as the codeword length is increased. The practical realization of such a code requi res the design of a pair of channel codes with unequal error protection (UEP) properties determined by the inter-source correlation and the channel capacity available to each source. Towards this end, a linear programming based procedure for jointly optimizing the degree profiles of a pair of irregular LDPC codes to achieve the required UEP properties is presented. Experimental results obtained with both binary symmetric channels and binary-input Gaussian channels are presented, which demonstrate that the proposed UEP-DJSC codes can significantly outperform separate source-channel codes, as well as previously reported joint source-channel coding schemes, particularly for short codeword lengths.

关键词： distributed source coding joint source-channel coding LDPC codes unequal error protection belief-propagation EXIT-chart analysis

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Operational Rate-Distortion Performance of Single-source and distributed Compressed Sensing

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IEEE TRANSACTIONS ON COMMUNICATIONS 2014年第6期62卷 2022-2033页

作者： Coluccia, Giulio Roumy, Aline Magli, Enrico Politecn Torino Dipartimento Elettron & Telecomunicaz I-10129 Turin Italy INRIA F-78153 Rennes France

We consider correlated and distributed sources without cooperation at the encoder. For these sources, we derive the best achievable performance in the rate-distortion sense of any distributed compressed sensing scheme, under the constraint of high-rate quantization. Moreover, under this model we derive a closed-form expression of the rate gain achieved by taking into account the correlation of the sources at the receiver and a closed-form expression of the average performance of the oracle receiver for independent and joint reconstruction. Finally, we show experimentally that the exploitation of the correlation between the sources performs close to optimal and that the only penalty is due to the missing knowledge of the sparsity support as in (non distributed) compressed sensing. Even if the derivation is performed in the large system regime, where signal and system parameters tend to infinity, numerical results show that the equations match simulations for parameter values of practical interest.

关键词： Compressed sensing distributed source coding rate-distortion function Slepian-Wolf coding

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distributed Joint source and Channel coding with Low-Density Parity-Check Codes

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IEEE COMMUNICATIONS LETTERS 2013年第12期17卷 2336-2339页

作者： Cen, Feng Tongji Univ Dept Control Sci & Engn Shanghai 200092 Peoples R China

Low-density parity-check (LDPC) codes with the parity-based approach for distributed joint source channel coding (DJSCC) with decoder side information is described in this letter. The parity-based approach is theoretical limit achievable. Different edge degree distributions are used for source variable nodes and parity variable nodes. Particularly, the codeword-averaged density evolution (CADE) is presented for asymmetrically correlated nonuniform sources over the asymmetric memoryless transmission channel. Extensive simulations show that the splitting of variable nodes can improve the coding efficiency of suboptimal codes and lower the error floor.

关键词： distributed joint source-channel coding distributed source coding density evolution low-density parity-check codes nonuniform sources

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