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Gabriella Olmo - One of the best experts on this subject based on the ideXlab platform.

  • IEEE COMMUNICATIONS LETTERS (ACCEPTED FOR PUBLICATION) 1 Distributed Arithmetic Coding
    2014
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo, Senior Member
    Abstract:

    Abstract—We propose a distributed binary Arithmetic Coder for Slepian-Wolf coding with deCoder side information, along with a soft joint deCoder. The proposed scheme provides several advantages over existing schemes, and its performance is equal to or better than that of an equivalent scheme based on turbo codes at short and medium block lengths. Index Terms—Distributed source coding, Arithmetic coding, Slepian-Wolf coding, Wyner-Ziv coding, compression. I. INTRODUCTION AND BACKGROUND Distributed source coding (DSC) considers a situation in which two (or more) statistically dependent data sources must be encoded by separate enCoders. DSC theory proves that separate encoding is optimal, provided that the sources ar

  • distributed Arithmetic coding for the slepian wolf problem
    IEEE Transactions on Signal Processing, 2009
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo
    Abstract:

    Distributed source coding schemes are typically based on the use of channels codes as source codes. In this paper we propose a new paradigm, named ldquodistributed Arithmetic coding,rdquo which extends Arithmetic codes to the distributed case employing sequential decoding aided by the side information. In particular, we introduce a distributed binary Arithmetic Coder for the Slepian-Wolf coding problem, along with a joint deCoder. The proposed scheme can be applied to two sources in both the asymmetric mode, wherein one source acts as side information, and the symmetric mode, wherein both sources are coded with ambiguity, at any combination of achievable rates. Distributed Arithmetic coding provides several advantages over existing Slepian-Wolf Coders, especially good performance at small block lengths, and the ability to incorporate arbitrary source models in the encoding process, e.g., context-based statistical models, in much the same way as a classical Arithmetic Coder. We have compared the performance of distributed Arithmetic coding with turbo codes and low-density parity-check codes, and found that the proposed approach is very competitive.

  • Distributed Arithmetic Coding for the Slepian–Wolf Problem
    IEEE Transactions on Signal Processing, 2009
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo
    Abstract:

    Distributed source coding schemes are typically based on the use of channels codes as source codes. In this paper we propose a new paradigm, named ldquodistributed Arithmetic coding,rdquo which extends Arithmetic codes to the distributed case employing sequential decoding aided by the side information. In particular, we introduce a distributed binary Arithmetic Coder for the Slepian-Wolf coding problem, along with a joint deCoder. The proposed scheme can be applied to two sources in both the asymmetric mode, wherein one source acts as side information, and the symmetric mode, wherein both sources are coded with ambiguity, at any combination of achievable rates. Distributed Arithmetic coding provides several advantages over existing Slepian-Wolf Coders, especially good performance at small block lengths, and the ability to incorporate arbitrary source models in the encoding process, e.g., context-based statistical models, in much the same way as a classical Arithmetic Coder. We have compared the performance of distributed Arithmetic coding with turbo codes and low-density parity-check codes, and found that the proposed approach is very competitive.

  • Distributed Arithmetic Coding
    IEEE Communications Letters, 2007
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo
    Abstract:

    We propose a distributed binary Arithmetic Coder for Slepian-Wolf coding with deCoder side information, along with a soft joint deCoder. The proposed scheme provides several advantages over existing schemes, and its performance is equal to or better than that of an equivalent scheme based on turbo codes at short and medium block lengths.

  • ICC - Joint source-channel iterative decoding of codes
    2004 IEEE International Conference on Communications (IEEE Cat. No.04CH37577), 2004
    Co-Authors: Marco Grangetto, B. Scanavino, Gabriella Olmo
    Abstract:

    In this paper an innovative joint source channel coding scheme is presented. The system is based on iterative soft decoding of Arithmetic codes, by means of a novel soft-in soft-out deCoder based on suboptimal search and pruning of a binary tree. An error resilient Arithmetic Coder with a forbidden symbol is used in order to improve the performance of the joint source/channel scheme. The performance in the case of transmission across the AWGN channel is evaluated in terms of frame error rate, and compared to a traditional separated approach. Finally the convergence property of the system is analyzed by means of the EXIT chart technique.

Marco Grangetto - One of the best experts on this subject based on the ideXlab platform.

  • IEEE COMMUNICATIONS LETTERS (ACCEPTED FOR PUBLICATION) 1 Distributed Arithmetic Coding
    2014
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo, Senior Member
    Abstract:

    Abstract—We propose a distributed binary Arithmetic Coder for Slepian-Wolf coding with deCoder side information, along with a soft joint deCoder. The proposed scheme provides several advantages over existing schemes, and its performance is equal to or better than that of an equivalent scheme based on turbo codes at short and medium block lengths. Index Terms—Distributed source coding, Arithmetic coding, Slepian-Wolf coding, Wyner-Ziv coding, compression. I. INTRODUCTION AND BACKGROUND Distributed source coding (DSC) considers a situation in which two (or more) statistically dependent data sources must be encoded by separate enCoders. DSC theory proves that separate encoding is optimal, provided that the sources ar

  • distributed Arithmetic coding for the slepian wolf problem
    IEEE Transactions on Signal Processing, 2009
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo
    Abstract:

    Distributed source coding schemes are typically based on the use of channels codes as source codes. In this paper we propose a new paradigm, named ldquodistributed Arithmetic coding,rdquo which extends Arithmetic codes to the distributed case employing sequential decoding aided by the side information. In particular, we introduce a distributed binary Arithmetic Coder for the Slepian-Wolf coding problem, along with a joint deCoder. The proposed scheme can be applied to two sources in both the asymmetric mode, wherein one source acts as side information, and the symmetric mode, wherein both sources are coded with ambiguity, at any combination of achievable rates. Distributed Arithmetic coding provides several advantages over existing Slepian-Wolf Coders, especially good performance at small block lengths, and the ability to incorporate arbitrary source models in the encoding process, e.g., context-based statistical models, in much the same way as a classical Arithmetic Coder. We have compared the performance of distributed Arithmetic coding with turbo codes and low-density parity-check codes, and found that the proposed approach is very competitive.

  • Distributed Arithmetic Coding for the Slepian–Wolf Problem
    IEEE Transactions on Signal Processing, 2009
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo
    Abstract:

    Distributed source coding schemes are typically based on the use of channels codes as source codes. In this paper we propose a new paradigm, named ldquodistributed Arithmetic coding,rdquo which extends Arithmetic codes to the distributed case employing sequential decoding aided by the side information. In particular, we introduce a distributed binary Arithmetic Coder for the Slepian-Wolf coding problem, along with a joint deCoder. The proposed scheme can be applied to two sources in both the asymmetric mode, wherein one source acts as side information, and the symmetric mode, wherein both sources are coded with ambiguity, at any combination of achievable rates. Distributed Arithmetic coding provides several advantages over existing Slepian-Wolf Coders, especially good performance at small block lengths, and the ability to incorporate arbitrary source models in the encoding process, e.g., context-based statistical models, in much the same way as a classical Arithmetic Coder. We have compared the performance of distributed Arithmetic coding with turbo codes and low-density parity-check codes, and found that the proposed approach is very competitive.

  • Distributed Arithmetic Coding
    IEEE Communications Letters, 2007
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo
    Abstract:

    We propose a distributed binary Arithmetic Coder for Slepian-Wolf coding with deCoder side information, along with a soft joint deCoder. The proposed scheme provides several advantages over existing schemes, and its performance is equal to or better than that of an equivalent scheme based on turbo codes at short and medium block lengths.

  • selective encryption of jpeg 2000 images by means of randomized Arithmetic coding
    Multimedia Signal Processing, 2004
    Co-Authors: Marco Grangetto, A Grosso, Enrico Magli
    Abstract:

    We describe a novel multimedia security framework based on a modification of the Arithmetic Coder, which is used by most international image and video coding standards as entropy coding stage. In particular, we propose a randomized Arithmetic coding paradigm, which achieves encryption by randomly swapping the intervals of the least and most probable symbols in Arithmetic coding; moreover, we describe an implementation tailored to the JPEG 2000 standard. The proposed approach turns out to be robust towards attempts to discover the key, and allows very flexible procedures for insertion of redundancy at the codeblock level, allowing to perform total and selective encryption, conditional access, and encryption of regions of interest.

Enrico Magli - One of the best experts on this subject based on the ideXlab platform.

  • IEEE COMMUNICATIONS LETTERS (ACCEPTED FOR PUBLICATION) 1 Distributed Arithmetic Coding
    2014
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo, Senior Member
    Abstract:

    Abstract—We propose a distributed binary Arithmetic Coder for Slepian-Wolf coding with deCoder side information, along with a soft joint deCoder. The proposed scheme provides several advantages over existing schemes, and its performance is equal to or better than that of an equivalent scheme based on turbo codes at short and medium block lengths. Index Terms—Distributed source coding, Arithmetic coding, Slepian-Wolf coding, Wyner-Ziv coding, compression. I. INTRODUCTION AND BACKGROUND Distributed source coding (DSC) considers a situation in which two (or more) statistically dependent data sources must be encoded by separate enCoders. DSC theory proves that separate encoding is optimal, provided that the sources ar

  • distributed Arithmetic coding for the slepian wolf problem
    IEEE Transactions on Signal Processing, 2009
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo
    Abstract:

    Distributed source coding schemes are typically based on the use of channels codes as source codes. In this paper we propose a new paradigm, named ldquodistributed Arithmetic coding,rdquo which extends Arithmetic codes to the distributed case employing sequential decoding aided by the side information. In particular, we introduce a distributed binary Arithmetic Coder for the Slepian-Wolf coding problem, along with a joint deCoder. The proposed scheme can be applied to two sources in both the asymmetric mode, wherein one source acts as side information, and the symmetric mode, wherein both sources are coded with ambiguity, at any combination of achievable rates. Distributed Arithmetic coding provides several advantages over existing Slepian-Wolf Coders, especially good performance at small block lengths, and the ability to incorporate arbitrary source models in the encoding process, e.g., context-based statistical models, in much the same way as a classical Arithmetic Coder. We have compared the performance of distributed Arithmetic coding with turbo codes and low-density parity-check codes, and found that the proposed approach is very competitive.

  • Distributed Arithmetic Coding for the Slepian–Wolf Problem
    IEEE Transactions on Signal Processing, 2009
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo
    Abstract:

    Distributed source coding schemes are typically based on the use of channels codes as source codes. In this paper we propose a new paradigm, named ldquodistributed Arithmetic coding,rdquo which extends Arithmetic codes to the distributed case employing sequential decoding aided by the side information. In particular, we introduce a distributed binary Arithmetic Coder for the Slepian-Wolf coding problem, along with a joint deCoder. The proposed scheme can be applied to two sources in both the asymmetric mode, wherein one source acts as side information, and the symmetric mode, wherein both sources are coded with ambiguity, at any combination of achievable rates. Distributed Arithmetic coding provides several advantages over existing Slepian-Wolf Coders, especially good performance at small block lengths, and the ability to incorporate arbitrary source models in the encoding process, e.g., context-based statistical models, in much the same way as a classical Arithmetic Coder. We have compared the performance of distributed Arithmetic coding with turbo codes and low-density parity-check codes, and found that the proposed approach is very competitive.

  • Distributed Arithmetic Coding
    IEEE Communications Letters, 2007
    Co-Authors: Marco Grangetto, Enrico Magli, Gabriella Olmo
    Abstract:

    We propose a distributed binary Arithmetic Coder for Slepian-Wolf coding with deCoder side information, along with a soft joint deCoder. The proposed scheme provides several advantages over existing schemes, and its performance is equal to or better than that of an equivalent scheme based on turbo codes at short and medium block lengths.

  • selective encryption of jpeg 2000 images by means of randomized Arithmetic coding
    Multimedia Signal Processing, 2004
    Co-Authors: Marco Grangetto, A Grosso, Enrico Magli
    Abstract:

    We describe a novel multimedia security framework based on a modification of the Arithmetic Coder, which is used by most international image and video coding standards as entropy coding stage. In particular, we propose a randomized Arithmetic coding paradigm, which achieves encryption by randomly swapping the intervals of the least and most probable symbols in Arithmetic coding; moreover, we describe an implementation tailored to the JPEG 2000 standard. The proposed approach turns out to be robust towards attempts to discover the key, and allows very flexible procedures for insertion of redundancy at the codeblock level, allowing to perform total and selective encryption, conditional access, and encryption of regions of interest.

Grzegorz Pastuszak - One of the best experts on this subject based on the ideXlab platform.

  • generative multi symbol architecture of the binary Arithmetic Coder for uhdtv video enCoders
    IEEE Transactions on Circuits and Systems I-regular Papers, 2020
    Co-Authors: Grzegorz Pastuszak
    Abstract:

    Binary Arithmetic coding is a key part of recent video compression standards. Its throughput is limited by the inherent dependencies existing in the algorithm. As a consequence, a higher bin parallelism leads to lower clock frequencies. This paper presents an architecture able to exceed limits existing in previous hardware implementations. The architecture exploits less probable symbols as starting points for long series of bins coded in one clock cycle. The evaluation for four possible cases of the range value allows its update in the pipeline before the delayed selection based on actual value. The adaptive division into series is proposed to make long series more frequent. To shorten critical paths, rMPS variables computed for symbols coded in the same clock cycle are first summed and then added to the low register. Up to 16 bypass-mode symbols can be processed in parallel with context-coded symbols in one clock cycle. The architecture is generative, i.e., its throughput can be scaled with resources without strict limits. For example, the binary Arithmetic Coder synthesized on 90nm TSMC technology which consumes 101.4k gates and operates at the 570 MHz has the average throughput of 13.4 bins per clock cycle for the high-quality H.265/HEVC compression.

  • a novel architecture of Arithmetic Coder in jpeg2000 based on parallel symbol encoding
    Parallel Computing in Electrical Engineering, 2004
    Co-Authors: Grzegorz Pastuszak
    Abstract:

    This paper presents a high-performance architecture of the context adaptive binary Arithmetic Coder (CABAC) for the embedded block-coding algorithm in JPEG 2000. The architecture has been developed in two variants to code two or three context-symbol pairs per clock cycle. The inverse multiple branch selection (IMBS) method is proposed to minimize critical paths, which originate from causally dependent operations. The designs have been implemented in VHDL and synthesized for FPGA devices. Simulation results show that the two- and three-symbol engines can process about 22 million samples at 77 and 53 MHz working frequency, respectively.

  • a high performance architecture of Arithmetic Coder in jpeg2000
    International Conference on Multimedia and Expo, 2004
    Co-Authors: Grzegorz Pastuszak
    Abstract:

    This paper presents a high-performance architecture of the Arithmetic Coder for the embedded block coding algorithm in JPEG2000. The dedicated pipeline architecture, enhanced by the inverse multiple branch selection (IMBS) method, is proposed to code two context-symbol pairs per clock cycle. The overall design was implemented in VHDL and synthesized for FPGA devices. Simulation results show that it can process about 17 million samples at 77 MHz working frequency

  • high efficient architectures of the context adaptive binary Arithmetic Coder for h 264 avc
    International workshopon systems signals and image processing ambient multimedia, 2004
    Co-Authors: Grzegorz Pastuszak
    Abstract:

    This paper presents architecture design of the context adaptive binary Arithmetic coding (CABAC) in H.264/AVC. The pipelined architecture has been implemented in two variants targeting Altera FPGA Stratix devices. The first one process one symbol per clock cycle at the working frequency of 140 MHz. The second accepts two symbols per clock cycle at the frequency of 100 MHz. Evaluation results show that the engines meets throughput requirements of real-time television systems such as: PAL, NTSC, and even HDTV.

Bormin Huang - One of the best experts on this subject based on the ideXlab platform.

  • Ultraspectral sounder data compression using a novel marker-based error-resilient Arithmetic Coder
    Proceedings of SPIE, 2006
    Co-Authors: Bormin Huang, Y. Sriraja
    Abstract:

    Entropy coding techniques aim to achieve the entropy of the source data by assigning variable-length codewords to symbols with the code lengths linked to the corresponding symbol probabilities. Entropy Coders (e.g. Huffman coding, Arithmetic coding), in one form or the other, are commonly used as the last stage in various compression schemes. While these variable-length Coders provide better compression than fixed-length Coders, they are vulnerable to transmission errors. Even a single bit error in the transmission process can cause havoc in the subsequent decoded stream. To cope with it, this research proposes a marker-based sentinel mechanism in entropy coding for error detection and recovery. We use Arithmetic coding as an example to demonstrate this error-resilient technique for entropy coding. Experimental results on ultraspectral sounder data indicate that the marker-based error-resilient Arithmetic Coder provides remarkable robustness to correct transmission errors without significantly compromising the compression gains.

  • lossless compression of ultraspectral sounder data using an error resilient Arithmetic Coder
    Proceedings of SPIE, 2005
    Co-Authors: Shihchieh Wei, Bormin Huang
    Abstract:

    In lossless compression of the ultraspectral sounder data, the Arithmetic Coder is often used as the last stage of the compression scheme. While the Arithmetic Coder is good at compressing arbitrarily close to the entropy of the source, it is also known for its severe weakness to transmission noise. Even a single bit error in the transmission process can cause havoc and make the subsequent decoded stream completely useless. To cope with it, this paper adopts an Arithmetic Coder with a forbidden symbol and uses the maximum a posteriori (MAP) technique for decoding. Based on the ultraspectral sounder data, evaluation on the error correction capability of this error-resilient Arithmetic Coder will be reported.© (2005) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.