The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
Amir Said - One of the best experts on this subject based on the ideXlab platform.
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image wavelet coding systems part ii of Set Partition coding and image wavelet coding systems
Foundations and Trends in Signal Processing, 2008Co-Authors: William A Pearlman, Amir SaidAbstract:This monograph describes current-day wavelet transform image coding systems. As in the first part, steps of the algorithms are explained thoroughly and Set apart. An image coding system consists of several stages: transformation, quantization, Set Partition or adaptive entropy coding or both, decoding including rate control, inverse transformation, de-quantization, and optional processing (see Figure 1.6). Wavelet transform systems can provide many desirable properties besides high efficiency, such as scalability in quality, scalability in resolution, and region-of-interest access to the coded bitstream. These properties are built into the JPEG2000 standard, so its coding will be fully described. Since JPEG2000 codes subblocks of subbands, other methods, such as SBHP (Subband Block Hierarchical Partitioning) [3] and EZBC (Embedded Zero Block Coder) [8], that code subbands or its subblocks independently are also described. The emphasis in this part is the use of the basic algorithms presented in the previous part in ways that achieve these desirable bitstream properties. In this vein, we describe a modification of the tree-based coding in SPIHT (Set Partitioning In Hierarchical Trees) [15], whose output bitstream can be decoded partially corresponding to a designated region of interest and is simultaneously quality and resolution scalable. This monograph is extracted and adapted from the forthcoming textbook entitled Digital Signal Compression: Principles and Practice by William A. Pearlman and Amir Said, Cambridge University Press, 2009.
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Set Partition coding part i of Set Partition coding and image wavelet coding systems
Foundations and Trends in Signal Processing, 2008Co-Authors: William A Pearlman, Amir SaidAbstract:The purpose of this two-part monograph is to present a tutorial on Set Partition coding, with emphasis and examples on image wavelet transform coding systems, and describe their use in modern image coding systems. Set Partition coding is a procedure that recursively splits groups of integer data or transform elements guided by a sequence of threshold tests, producing groups of elements whose magnitudes are between two known thresholds, therefore, Setting the maximum number of bits required for their binary representation. It produces groups of elements whose magnitudes are less than a certain known threshold. Therefore, the number of bits for representing an element in a particular group is no more than the base-2 logarithm of its threshold rounded up to the nearest integer. SPIHT (Set Partitioning in Hierarchical Trees) and SPECK (Set Partitioning Embedded blocK) are popular state-of-the-art image coders that use Set Partition coding as the primary entropy coding method. JPEG2000 and EZW (Embedded Zerotree Wavelet) use it in an auxiliary manner. Part I elucidates the fundamentals of Set Partition coding and explains the Setting of thresholds and the block and tree modes of Partitioning. Algorithms are presented for the techniques of AGP (Amplitude and Group Partitioning), SPIHT, SPECK, and EZW. Numerical examples are worked out in detail for the latter three techniques. Part II describes various wavelet image coding systems that use Set Partitioning primarily, such as SBHP (Subband Block Hierarchical Partitioning), SPIHT, and EZBC (Embedded Zero-Block Coder). The basic JPEG2000 coder is also described. The coding procedures and the specific methods are presented both logically and in algorithmic form, where possible. Besides the obvious objective of obtaining small file sizes, much emphasis is placed on achieving low computational complexity and desirable output bitstream attributes, such as embeddedness, scalability in resolution, and random access decodability. This monograph is extracted and adapted from the forthcoming textbook entitled Digital Signal Compression: Principles and Practice by William A. Pearlman and Amir Said, Cambridge University Press, 2009.
M. Umemoto - One of the best experts on this subject based on the ideXlab platform.
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Structured Set Partitions and multilevel concatenated coding for partial response channels
IEEE Transactions on Communications, 1999Co-Authors: A.v. Kuznetsov, M. UmemotoAbstract:We present a systematic way to construct multilevel concatenated codes for partial response (PR) channels using: (1) a structured Set Partition (SSP) of multiple channel output Sets and (2) a Set of conventional block codes with different error correcting capabilities. A lower bound on the minimum squared Euclidean distance of the constructed codes is given. This bound is based on the interSet minimal Euclidean distances of the SSP and the minimum Hamming distances of the used block codes. An example of SSP for the extended class 4 partial response channel (EPR4) is presented. Iterative suboptimal decoding, which combines Viterbi detection on the trellis of the PR channel with algebraic error detection/correction, can be applied to the constructed concatenated codes. Truncated versions of the iterative decoding scheme are simulated and compared with each other.
A.v. Kuznetsov - One of the best experts on this subject based on the ideXlab platform.
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Structured Set Partitions and multilevel concatenated coding for partial response channels
IEEE Transactions on Communications, 1999Co-Authors: A.v. Kuznetsov, M. UmemotoAbstract:We present a systematic way to construct multilevel concatenated codes for partial response (PR) channels using: (1) a structured Set Partition (SSP) of multiple channel output Sets and (2) a Set of conventional block codes with different error correcting capabilities. A lower bound on the minimum squared Euclidean distance of the constructed codes is given. This bound is based on the interSet minimal Euclidean distances of the SSP and the minimum Hamming distances of the used block codes. An example of SSP for the extended class 4 partial response channel (EPR4) is presented. Iterative suboptimal decoding, which combines Viterbi detection on the trellis of the PR channel with algebraic error detection/correction, can be applied to the constructed concatenated codes. Truncated versions of the iterative decoding scheme are simulated and compared with each other.
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Structured Set Partitions for high-order partial response channels
Proceedings of the 1999 IEEE Information Theory and Communications Workshop (Cat. No. 99EX253), 1Co-Authors: A.v. KuznetsovAbstract:Multilevel modulation codes for partial response (PR) channels can be constructed using a structured Set Partition (SSP) of channel output words, and a Set of block codes with different error correcting capabilities. We present SSP for the classical and modified E/sup 2/PR4 channels. The coding gain 3.5 dB can be achieved at the linear density 2.8 for ME/sup 2/PR channel with the target [5,4,-3,-4,-2] given by Sawaguchi et al. (see Proc. GLOBCOM-98, 1998).
William A Pearlman - One of the best experts on this subject based on the ideXlab platform.
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motion differential Set Partition coding for image sequence and video compression
Journal of Visual Communication and Image Representation, 2012Co-Authors: William A PearlmanAbstract:Efficient image sequence coding exploits both intra- and inter-frame correlations. Set Partition coding (SPC) is efficient in intra-frame de-correlation for still images. Based on SPC, a novel image sequence coding system, called motion differential SPC (M-D-SPC), is presented in this paper. It removes inter-frame redundancy by re-using the significance map of a previously SPC coded frame. Every frame is encoded and decoded separate from other frames. Furthermore, there is no reconstruction of encoded frames in the encoder, as is done with interframe prediction methods. The M-D-SPC exhibits an auxiliary key frame coding framework, which achieves higher coding efficiency compared to the all-intra-coding schemes and meanwhile maintains the beneficial features of SPC all-intra-coding, such as computational simplicity, rate scalability, error non-propagation, and random frame access. SPIHT-based simulations on hyperspectral images, 3D/4D medical images, and video show greater compression efficiency than the standard intraframe coding method of motion JPEG2000.
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image wavelet coding systems part ii of Set Partition coding and image wavelet coding systems
Foundations and Trends in Signal Processing, 2008Co-Authors: William A Pearlman, Amir SaidAbstract:This monograph describes current-day wavelet transform image coding systems. As in the first part, steps of the algorithms are explained thoroughly and Set apart. An image coding system consists of several stages: transformation, quantization, Set Partition or adaptive entropy coding or both, decoding including rate control, inverse transformation, de-quantization, and optional processing (see Figure 1.6). Wavelet transform systems can provide many desirable properties besides high efficiency, such as scalability in quality, scalability in resolution, and region-of-interest access to the coded bitstream. These properties are built into the JPEG2000 standard, so its coding will be fully described. Since JPEG2000 codes subblocks of subbands, other methods, such as SBHP (Subband Block Hierarchical Partitioning) [3] and EZBC (Embedded Zero Block Coder) [8], that code subbands or its subblocks independently are also described. The emphasis in this part is the use of the basic algorithms presented in the previous part in ways that achieve these desirable bitstream properties. In this vein, we describe a modification of the tree-based coding in SPIHT (Set Partitioning In Hierarchical Trees) [15], whose output bitstream can be decoded partially corresponding to a designated region of interest and is simultaneously quality and resolution scalable. This monograph is extracted and adapted from the forthcoming textbook entitled Digital Signal Compression: Principles and Practice by William A. Pearlman and Amir Said, Cambridge University Press, 2009.
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Set Partition coding part i of Set Partition coding and image wavelet coding systems
Foundations and Trends in Signal Processing, 2008Co-Authors: William A Pearlman, Amir SaidAbstract:The purpose of this two-part monograph is to present a tutorial on Set Partition coding, with emphasis and examples on image wavelet transform coding systems, and describe their use in modern image coding systems. Set Partition coding is a procedure that recursively splits groups of integer data or transform elements guided by a sequence of threshold tests, producing groups of elements whose magnitudes are between two known thresholds, therefore, Setting the maximum number of bits required for their binary representation. It produces groups of elements whose magnitudes are less than a certain known threshold. Therefore, the number of bits for representing an element in a particular group is no more than the base-2 logarithm of its threshold rounded up to the nearest integer. SPIHT (Set Partitioning in Hierarchical Trees) and SPECK (Set Partitioning Embedded blocK) are popular state-of-the-art image coders that use Set Partition coding as the primary entropy coding method. JPEG2000 and EZW (Embedded Zerotree Wavelet) use it in an auxiliary manner. Part I elucidates the fundamentals of Set Partition coding and explains the Setting of thresholds and the block and tree modes of Partitioning. Algorithms are presented for the techniques of AGP (Amplitude and Group Partitioning), SPIHT, SPECK, and EZW. Numerical examples are worked out in detail for the latter three techniques. Part II describes various wavelet image coding systems that use Set Partitioning primarily, such as SBHP (Subband Block Hierarchical Partitioning), SPIHT, and EZBC (Embedded Zero-Block Coder). The basic JPEG2000 coder is also described. The coding procedures and the specific methods are presented both logically and in algorithmic form, where possible. Besides the obvious objective of obtaining small file sizes, much emphasis is placed on achieving low computational complexity and desirable output bitstream attributes, such as embeddedness, scalability in resolution, and random access decodability. This monograph is extracted and adapted from the forthcoming textbook entitled Digital Signal Compression: Principles and Practice by William A. Pearlman and Amir Said, Cambridge University Press, 2009.
Francois Theberge - One of the best experts on this subject based on the ideXlab platform.
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comparing graph clusterings Set Partition measures vs graph aware measures
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020Co-Authors: Valerie Poulin, Francois ThebergeAbstract:In this paper, we propose a family of graph Partition similarity measures that take the topology of the graph into account. These graph-aware measures are alternatives to using Set Partition similarity measures that are not specifically designed for graphs. The two types of measures, graph-aware and Set Partition measures, are shown to have opposite behaviors with respect to resolution issues and provide complementary information necessary to compare graph Partitions.
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comparing graph clusterings Set Partition measures vs graph aware measures
arXiv: Learning, 2018Co-Authors: Valerie Poulin, Francois ThebergeAbstract:In this paper, we propose a family of graph Partition similarity measures that take the topology of the graph into account. These graph-aware measures are alternatives to using Set Partition similarity measures that are not specifically designed for graph Partitions. The two types of measures, graph-aware and Set Partition measures, are shown to have opposite behaviors with respect to resolution issues and provide complementary information necessary to assess that two graph Partitions are similar.
