The Experts below are selected from a list of 4734 Experts worldwide ranked by ideXlab platform

Ram Zamir - One of the best experts on this subject based on the ideXlab platform.

  • Joint Wyner–Ziv/Dirty-Paper Coding by Modulo-Lattice Modulation
    IEEE Transactions on Information Theory, 2009
    Co-Authors: Yuval Kochman, Ram Zamir
    Abstract:

    The combination of source coding with decoder Side information (the Wyner-Ziv problem) and channel coding with Encoder Side information (the Gel'fand-Pinsker problem) can be optimally solved using the separation principle. In this work, we show an alternative scheme for the quadratic-Gaussian case, which merges source and channel coding. This scheme achieves the optimal performance by applying a modulo-lattice modulation to the analog source. Thus, it saves the complexity of quantization and channel decoding, and remains with the task of ldquoshapingrdquo only. Furthermore, for high signal-to-noise ratio (SNR), the scheme approaches the optimal performance using an SNR-independent Encoder, thus it proves for this special case the feasibility of universal joint source-channel coding.

  • Joint Wyner-Ziv/Dirty Paper coding by modulo-lattice modulation
    arXiv: Information Theory, 2008
    Co-Authors: Yuval Kochman, Ram Zamir
    Abstract:

    The combination of source coding with decoder Side-information (Wyner-Ziv problem) and channel coding with Encoder Side-information (Gel'fand-Pinsker problem) can be optimally solved using the separation principle. In this work we show an alternative scheme for the quadratic-Gaussian case, which merges source and channel coding. This scheme achieves the optimal performance by a applying modulo-lattice modulation to the analog source. Thus it saves the complexity of quantization and channel decoding, and remains with the task of "shaping" only. Furthermore, for high signal-to-noise ratio (SNR), the scheme approaches the optimal performance using an SNR-independent Encoder, thus it is robust to unknown SNR at the Encoder.

  • Source Coding With Encoder Side Information
    arXiv: Information Theory, 2004
    Co-Authors: Emin Martinian, Gregory W. Wornell, Ram Zamir
    Abstract:

    We introduce the idea of distortion Side information, which does not directly depend on the source but instead affects the distortion measure. We show that such distortion Side information is not only useful at the Encoder, but that under certain conditions, knowing it at only the Encoder is as good as knowing it at both Encoder and decoder, and knowing it at only the decoder is useless. Thus distortion Side information is a natural complement to the signal Side information studied by Wyner and Ziv, which depends on the source but does not involve the distortion measure. Furthermore, when both types of Side information are present, we characterize the penalty for deviating from the configuration of Encoder-only distortion Side information and decoder-only signal Side information, which in many cases is as good as full Side information knowledge.

  • Source Coding With Distortion Side Information At The Encoder
    arXiv: Information Theory, 2004
    Co-Authors: Emin Martinian, Gregory W. Wornell, Ram Zamir
    Abstract:

    We conSider lossy source coding when Side information affecting the distortion measure may be available at the Encoder, decoder, both, or neither. For example, such distortion Side information can model reliabilities for noisy measurements, sensor calibration information, or perceptual effects like masking and sensitivity to context. When the distortion Side information is statistically independent of the source, we show that in many cases (e.g, for additive or multiplicative distortion Side information) there is no penalty for knowing the Side information only at the Encoder, and there is no advantage to knowing it at the decoder. Furthermore, for quadratic distortion measures scaled by the distortion Side information, we evaluate the penalty for lack of Encoder knowledge and show that it can be arbitrarily large. In this scenario, we also sketch transform based quantizers constructions which efficiently exploit Encoder Side information in the high-resolution limit.

  • Encoder Side information is useful in source coding
    International Symposium on Information Theory, 2004
    Co-Authors: E Martinan, Gregory W. Wornell, Ram Zamir
    Abstract:

    We introduce the idea of distortion Side information, which does not directly depend on the source but instead affects the distortion measure. Such Side information is not only useful at the Encoder, but under many conditions of interest, knowing it at the Encoder alone is sufficient and knowing it at the decoder alone is useless.

Olivier Deforges - One of the best experts on this subject based on the ideXlab platform.

  • Adaptive pixel/patch-based synthesis for texture compression
    2011
    Co-Authors: Fabien Racape, Simon Lefort, Marie Babel, Edouard Francois, Olivier Deforges
    Abstract:

    This paper presents an adaptive scheme for synthesizing missing textured regions. In synthesis-based compression approaches, large textures are removed at Encoder Side and filled in at decoder Side. This work proposes a synthesizer in which both complementary pixel-based and patch-based approaches are used. According to results shown by synthesis algorithms, patch-based and pixel-based approaches are efficient with different kinds of texture. Two algorithms are adapted to the region synthesis context: the sample patch is built from surrounding texture and potential anchor blocks inSide the removed region; the scan order depends on a confidence map in order to take advantage of the designed patch; DCT-descriptors provide the minimum size of matching window which is a required parameter for both synthesizers. Finally an "a posteriori" gradient based assessor enables the synthesizer to switch between algorithms.

  • EUSIPCO - Characterization and adaptive texture synthesis-based compression scheme
    2011
    Co-Authors: Fabien Racape, Dominique Thoreau, Simon Lefort, Marie Babel, Olivier Deforges
    Abstract:

    This paper presents an adaptive texture synthesis-based compression scheme, where textured regions are detected and removed at Encoder Side, allowing the decoder to use texture synthesis to fill them. The detection relies on locally adaptive resolution segmentation. According to results shown by synthesis algorithms, they need to be parameterized according to the patterns to be synthesized. In this framework, the synthesizer gets its parameters from DCT feature-based texture descriptors. An adaptive pixel-based algorithm is used, relying on the comparison between current pixel neighborhood and those in an atypically shaped sample. Different neighborhood sizes are conSidered to better catch texture patterns. The framework has been validated within an H.264/AVC video codec. Experimental results show significant bit-rate saving at similar visual quality.

  • Characterization and adaptive texture synthesis-based compression scheme
    2011
    Co-Authors: Fabien Racape, Dominique Thoreau, Simon Lefort, Marie Babel, Olivier Deforges
    Abstract:

    This paper presents an adaptive texture synthesis-based compression scheme, where textured regions are detected and removed at Encoder Side, allowing the decoder to use texture synthesis to fill them. The detection relies on locally adaptive resolution segmentation. According to results shown by synthesis algorithms, they need to be parameterized according to the patterns to be synthesized. In this framework, the synthesizer gets its parameters from DCT feature-based texture descriptors. An adaptive pixel-based algorithm is used, relying on the comparison between current pixel neighborhood and those in an atypically shaped sample. Different neighborhood sizes are conSidered to better match texture patterns. The framework has been validated within an H.264/AVC video codec. Experimental results show significant bit-rate saving at similar visual quality.

  • Texture refinement framework for improved video coding
    2010
    Co-Authors: Fabien Racape, Dominique Thoreau, Marie Babel, Olivier Deforges, Jérôme Viéron, Edouard Francois
    Abstract:

    H.264/AVC standard offers an efficient way of reducing the noticeable artefacts of former video coding schemes, but it can be perfectible for the coding of detailed texture areas. This paper presents a conceptual coding framework, utilizing visual perception redundancy, which aims at improving both bit-rate and quality on textured areas. The approach is generic and can be integrated into usual coding scheme. The proposed scheme is divided into three steps: a first algorithm analyses texture regions, with an eye to build a dictionary of the most representative texture sub-regions (RTS). The Encoder preserves then them at a higher quality than the rest of the picture, in order to enable a refinement algorithm to finally spread the preserved information over textured areas. In this paper, we present a first solution to validate the framework, detailing then the Encoder Side in order to define a simple method for dictionary building. The proposed H.264/AVC compliant scheme creates a dictionary of macroblocks

Yuval Kochman - One of the best experts on this subject based on the ideXlab platform.

  • Joint Wyner–Ziv/Dirty-Paper Coding by Modulo-Lattice Modulation
    IEEE Transactions on Information Theory, 2009
    Co-Authors: Yuval Kochman, Ram Zamir
    Abstract:

    The combination of source coding with decoder Side information (the Wyner-Ziv problem) and channel coding with Encoder Side information (the Gel'fand-Pinsker problem) can be optimally solved using the separation principle. In this work, we show an alternative scheme for the quadratic-Gaussian case, which merges source and channel coding. This scheme achieves the optimal performance by applying a modulo-lattice modulation to the analog source. Thus, it saves the complexity of quantization and channel decoding, and remains with the task of ldquoshapingrdquo only. Furthermore, for high signal-to-noise ratio (SNR), the scheme approaches the optimal performance using an SNR-independent Encoder, thus it proves for this special case the feasibility of universal joint source-channel coding.

  • Joint Wyner-Ziv/Dirty Paper coding by modulo-lattice modulation
    arXiv: Information Theory, 2008
    Co-Authors: Yuval Kochman, Ram Zamir
    Abstract:

    The combination of source coding with decoder Side-information (Wyner-Ziv problem) and channel coding with Encoder Side-information (Gel'fand-Pinsker problem) can be optimally solved using the separation principle. In this work we show an alternative scheme for the quadratic-Gaussian case, which merges source and channel coding. This scheme achieves the optimal performance by a applying modulo-lattice modulation to the analog source. Thus it saves the complexity of quantization and channel decoding, and remains with the task of "shaping" only. Furthermore, for high signal-to-noise ratio (SNR), the scheme approaches the optimal performance using an SNR-independent Encoder, thus it is robust to unknown SNR at the Encoder.

Ngi Ngan - One of the best experts on this subject based on the ideXlab platform.

  • ISCAS - Perceptual image compression via adaptive block- based super-resolution directed down-sampling
    2011 IEEE International Symposium of Circuits and Systems (ISCAS), 2011
    Co-Authors: Ngi Ngan
    Abstract:

    In this paper, we propose a novel perceptual image coding scheme via adaptive block-based super-resolution directed down-sampling. At the Encoder Side, for each macroblock of a given image, Rate Distortion Optimization (RDO) determines whether it is encoded at the original or down-sampled resolution. The down-sampling process is directed by super-resolution, which generates the down-sampled block by minimizing the reconstruction errors between the original macroblock and the one restored by the corresponding super-resolution method. At the decoder Side, in order to reduce the complexity, the super-resolution method reconstructs the full-resolution macroblock in the DCT domain together with the inverse DCT. Experimental results have demonstrated that the proposed method can produce higher quality images in terms of both PSNR and visual quality compared with the existing methods.

Fabien Racape - One of the best experts on this subject based on the ideXlab platform.

  • Adaptive pixel/patch-based synthesis for texture compression
    2011
    Co-Authors: Fabien Racape, Simon Lefort, Marie Babel, Edouard Francois, Olivier Deforges
    Abstract:

    This paper presents an adaptive scheme for synthesizing missing textured regions. In synthesis-based compression approaches, large textures are removed at Encoder Side and filled in at decoder Side. This work proposes a synthesizer in which both complementary pixel-based and patch-based approaches are used. According to results shown by synthesis algorithms, patch-based and pixel-based approaches are efficient with different kinds of texture. Two algorithms are adapted to the region synthesis context: the sample patch is built from surrounding texture and potential anchor blocks inSide the removed region; the scan order depends on a confidence map in order to take advantage of the designed patch; DCT-descriptors provide the minimum size of matching window which is a required parameter for both synthesizers. Finally an "a posteriori" gradient based assessor enables the synthesizer to switch between algorithms.

  • EUSIPCO - Characterization and adaptive texture synthesis-based compression scheme
    2011
    Co-Authors: Fabien Racape, Dominique Thoreau, Simon Lefort, Marie Babel, Olivier Deforges
    Abstract:

    This paper presents an adaptive texture synthesis-based compression scheme, where textured regions are detected and removed at Encoder Side, allowing the decoder to use texture synthesis to fill them. The detection relies on locally adaptive resolution segmentation. According to results shown by synthesis algorithms, they need to be parameterized according to the patterns to be synthesized. In this framework, the synthesizer gets its parameters from DCT feature-based texture descriptors. An adaptive pixel-based algorithm is used, relying on the comparison between current pixel neighborhood and those in an atypically shaped sample. Different neighborhood sizes are conSidered to better catch texture patterns. The framework has been validated within an H.264/AVC video codec. Experimental results show significant bit-rate saving at similar visual quality.

  • Characterization and adaptive texture synthesis-based compression scheme
    2011
    Co-Authors: Fabien Racape, Dominique Thoreau, Simon Lefort, Marie Babel, Olivier Deforges
    Abstract:

    This paper presents an adaptive texture synthesis-based compression scheme, where textured regions are detected and removed at Encoder Side, allowing the decoder to use texture synthesis to fill them. The detection relies on locally adaptive resolution segmentation. According to results shown by synthesis algorithms, they need to be parameterized according to the patterns to be synthesized. In this framework, the synthesizer gets its parameters from DCT feature-based texture descriptors. An adaptive pixel-based algorithm is used, relying on the comparison between current pixel neighborhood and those in an atypically shaped sample. Different neighborhood sizes are conSidered to better match texture patterns. The framework has been validated within an H.264/AVC video codec. Experimental results show significant bit-rate saving at similar visual quality.

  • Texture refinement framework for improved video coding
    2010
    Co-Authors: Fabien Racape, Dominique Thoreau, Marie Babel, Olivier Deforges, Jérôme Viéron, Edouard Francois
    Abstract:

    H.264/AVC standard offers an efficient way of reducing the noticeable artefacts of former video coding schemes, but it can be perfectible for the coding of detailed texture areas. This paper presents a conceptual coding framework, utilizing visual perception redundancy, which aims at improving both bit-rate and quality on textured areas. The approach is generic and can be integrated into usual coding scheme. The proposed scheme is divided into three steps: a first algorithm analyses texture regions, with an eye to build a dictionary of the most representative texture sub-regions (RTS). The Encoder preserves then them at a higher quality than the rest of the picture, in order to enable a refinement algorithm to finally spread the preserved information over textured areas. In this paper, we present a first solution to validate the framework, detailing then the Encoder Side in order to define a simple method for dictionary building. The proposed H.264/AVC compliant scheme creates a dictionary of macroblocks