The Experts below are selected from a list of 207 Experts worldwide ranked by ideXlab platform

Ali N. Akansu - One of the best experts on this subject based on the ideXlab platform.

  • Multiresolution Signal Decomposition (Second Edition) - Chapter 5 – Time-Frequency Representations
    Multiresolution Signal Decomposition, 2001
    Co-Authors: Ali N. Akansu, Richard A. Haddad
    Abstract:

    Time- and frequency-domain characterizations of a signal are not only important in filter design but also dictate the nature of signal processing (speech, image, video, etc.). Often signal operations, such as compression, excision, modulation, and feature extraction, can be performed more efficiently in one domain than the other. Nonstationary signals are signals whose salient features change with time and the traditional Fourier analysis is inadequate to deal with these signals. This chapter focuses on the description and evaluation of techniques for achieving time-frequency localization on discrete-time signals. The chapter reviews the classical analog uncertainty principle and the short-time Fourier transform. The chapter defines, calculate, and compare localization features of filter banks and standard Block Transforms; and it explores the role of tree-structured filter banks in achieving desired time-frequency resolution. The chapter discusses the way to achieve arbitrary “tiling” of the time-frequency plane using Block Transforms and the applications of this approach to signal compaction and to interference excision in spread spectrum communications systems.

  • wavelet subband and Block Transforms in communications and multimedia
    1999
    Co-Authors: Ali N. Akansu, Michael J Medley
    Abstract:

    From the Publisher: Wavelet and subband Transforms have been of great interest in the fields of engineering and applied mathematics. The theories of these powerful signal processing tools have matured and many applications utilizing them are emerging in different disciplines. This book, comprised of eleven chapter contributions from prominent researchers in the field, focuses on communications and multimedia applications of wavelet and subband Transforms. Wavelet, Subband and Block Transforms in Communications and Multimedia will be of particular interest to engineers and scientists who want to learn about state-of-the-art subband and wavelet transform applications as well as their theoretical underpinnings. It can also serve as a supplementary book for graduate level engineering and applied mathematics courses on wavelet and subband Transforms.

  • ICASSP (3) - An evaluation of time-frequency localization in Transforms and filter banks
    IEEE International Conference on Acoustics Speech and Signal Processing, 1993
    Co-Authors: Y. Liu, Ali N. Akansu
    Abstract:

    The authors derive the discrete-time uncertainty and evaluate the time-frequency localizations of orthogonal bases. They measure and compare the localization features of known Block Transforms, filter banks, and wavelet filters. It is emphasized that the time and frequency behaviors of basis functions should be considered simultaneously in the design of Block Transforms and filter banks for further improvements in their applications. >

  • On Lapped Orthogonal Transforms
    1992
    Co-Authors: Ali N. Akansu, Frank E. Wadas
    Abstract:

    The energy compaction performance of several lapped or- thogonal Transforms (LOT's) are presented in this correspondence. It is shown that the LOT outperforms the conventional Block Transforms for all the cases considered. The performance of the poorly performing Block Transforms for high correlation sources increased dramatically in their LOT versions. It is found that the energy compaction perfor- mance of the LOT versions of different Block Transforms considered is about the same. Therefore, the choice of LOT is based on the efficiency of the transform algorithm. The LOT is an alternative to the Block Transforms for signal coding applications. Also, the Blocking effect is reduced with the increase in the computational complexity of the trans- form algorithm.

  • On lapped orthogonal Transforms (signal coding applications)
    IEEE Transactions on Signal Processing, 1992
    Co-Authors: Ali N. Akansu, Frank E. Wadas
    Abstract:

    The energy compaction performance of several lapped orthogonal Transforms (LOTs) are presented. It is shown that the LOT outperforms the conventional Block Transforms for all the cases considered. The performance of the poorly performing Block Transforms for high correlation sources increased dramatically in their LOT versions. It is found that the energy compaction performance of the LOT versions of the different Block Transforms considered is about the same. Therefore, the choice of LOT is based on the efficiency of the transform algorithm. The LOT is an alternative to the Block Transforms for signal coding applications. Also, the Blocking effect is reduced with the increase in the computational complexity of the transform algorithm. >

Michael J Medley - One of the best experts on this subject based on the ideXlab platform.

  • Interference Mitigation in Spread Spectrum Systems Using Lapped Transforms
    2002
    Co-Authors: Michael J Medley
    Abstract:

    Abstract : In this report, linear and non-linear transform domain filtering techniques are examined and proposed as a means of enhancing the inherent interference immunity associated with direct sequence spread spectrum communication receivers. This analysis begins with a review of Block transform domain Wiener filters and is further developed in the lapped transform domain. The latter part of this report addresses the use of lapped Transforms to transform the received data signal into the transform domain wherein adaptive excision is performed. System performance results are presented for a variety of channel conditions and compared to those obtained using orthonormal Block Transforms. These results demonstrate the improved performance and increased robustness with respect to jammer frequency and bandwidth of lapped transform domain excision techniques relative to similar algorithms based on non-weighted Block Transforms.

  • wavelet subband and Block Transforms in communications and multimedia
    1999
    Co-Authors: Ali N. Akansu, Michael J Medley
    Abstract:

    From the Publisher: Wavelet and subband Transforms have been of great interest in the fields of engineering and applied mathematics. The theories of these powerful signal processing tools have matured and many applications utilizing them are emerging in different disciplines. This book, comprised of eleven chapter contributions from prominent researchers in the field, focuses on communications and multimedia applications of wavelet and subband Transforms. Wavelet, Subband and Block Transforms in Communications and Multimedia will be of particular interest to engineers and scientists who want to learn about state-of-the-art subband and wavelet transform applications as well as their theoretical underpinnings. It can also serve as a supplementary book for graduate level engineering and applied mathematics courses on wavelet and subband Transforms.

  • Narrow-band interference excision in spread spectrum systems using lapped Transforms
    IEEE Transactions on Communications, 1997
    Co-Authors: Michael J Medley, Gary J. Saulnier, Pankaj K. Das
    Abstract:

    In order to mitigate narrow-band interference in spread spectrum communications systems, novel communications receivers incorporating transform domain filtering techniques are designed. In this paper, lapped Transforms are used to transform the received data signal to the transform domain wherein adaptive excision is performed. Transform domain detection algorithms, which yield bit decisions based on the remaining signal energy, are analyzed and, together with excision, are employed on a Block-by-Block basis to suppress single-tone and narrow-band Gaussian interference. System performance is analytically quantified in terms of the overall system bit-error rate (BER). Subsequent results are presented for a variety of channel conditions and compared to those obtained using excision algorithms based on orthonormal Block Transforms (Medley 1995). These results demonstrate the improved performance and increased robustness with respect to jammer frequency and bandwidth of lapped transform domain excision techniques relative to similar algorithms based on nonweighted Block Transforms.

Moon Ho Lee - One of the best experts on this subject based on the ideXlab platform.

  • Quantum codes based on fast pauli Block Transforms in the finite field
    Quantum Information Processing, 2010
    Co-Authors: Ronghua Shi, Ying Guo, Moon Ho Lee
    Abstract:

    Motivated by the fast Pauli Block Transforms (or matrices) over the finite field GF(q) for an arbitrary number q, we suggest how to construct the simplified quantum code on the basis of quadratic residues. The present quantum code, which is the stabilizer quantum code, can be fast generated from an Abelian group with commutative quantum operators being selected from a suitable Pauli Block matrix. This construction does not require the dual-containing or self-orthogonal constraint for the standard quantum error-correction code, thus allowing us to construct a quantum code with much efficiency.

  • Fast Constructions of Quantum Codes Based on Residues Pauli Block Matrices
    Advances in Mathematical Physics, 2010
    Co-Authors: Ying Guo, Guihu Zeng, Moon Ho Lee
    Abstract:

    We demonstrate how to fast construct quantum error-correction codes based on quadratic residues Pauli Block Transforms. The present quantum codes have an advantage of being fast designed from Abelian groups on the basis of Pauli Block matrices that can be yielded from quadratic residues with much efficiency.

Philip A Chou - One of the best experts on this subject based on the ideXlab platform.

  • Region adaptive graph fourier transform for 3d point clouds
    arXiv: Computer Vision and Pattern Recognition, 2020
    Co-Authors: Eduardo Pavez, Benjamin Girault, Antonio Ortega, Philip A Chou
    Abstract:

    We introduce the Region Adaptive Graph Fourier Transform (RA-GFT) for compression of 3D point cloud attributes. The RA-GFT is a multiresolution transform, formed by combining spatially localized Block Transforms. We assume the points are organized by a family of nested partitions represented by a rooted tree. At each resolution level, attributes are processed in clusters using Block Transforms. Each Block transform produces a single approximation (DC) coefficient, and various detail (AC) coefficients. The DC coefficients are promoted up the tree to the next (lower resolution) level, where the process can be repeated until reaching the root. Since clusters may have a different numbers of points, each Block transform must incorporate the relative importance of each coefficient. For this, we introduce the $\mathbf{Q}$-normalized graph Laplacian, and propose using its eigenvectors as the Block transform. The RA-GFT achieves better complexity-performance trade-offs than previous approaches. In particular, it outperforms the Region Adaptive Haar Transform (RAHT) by up to 2.5 dB, with a small complexity overhead.

  • ICIP - Region Adaptive Graph Fourier Transform for 3D Point Clouds
    2020 IEEE International Conference on Image Processing (ICIP), 2020
    Co-Authors: Eduardo Pavez, Benjamin Girault, Antonio Ortega, Philip A Chou
    Abstract:

    We introduce the Region Adaptive Graph Fourier Transform (RAGFT) for compression of 3D point cloud attributes. The RA-GFT is a multiresolution transform, formed by combining spatially localized Block Transforms. We assume the points are organized by a family of nested partitions represented by a rooted tree. At each resolution level, attributes are processed in clusters using Block Transforms. Each Block transform produces a single approximation (DC) coefficient, and various detail (AC) coefficients. The DC coefficients are promoted up the tree to the next (lower resolution) level, where the process can be repeated until reaching the root. Since clusters may have a different numbers of points, each Block transform must incorporate the relative importance of each coefficient. For this, we introduce the Q-normalized graph Laplacian, and propose using its eigenvectors as the Block transform. The RA-GFT achieves better complexity-performance trade-offs than previous approaches. In particular, it outperforms the Region Adaptive Haar Transform (RAHT) by up to 2.5 dB, with a small complexity overhead.

  • hierarchical vector quantization of perceptually weighted Block Transforms
    Data Compression Conference, 1995
    Co-Authors: N Chaddha, Mohan Vishwanath, Philip A Chou
    Abstract:

    This paper presents techniques for the design of generic Block transform based vector quantizer encoders implemented by table lookups. In these table lookup encoders, input vectors to the encoders are used directly as addresses in code tables to choose the codewords. There is no need to perform the forward or reverse Transforms. They are implemented in the tables. In order to preserve manageable table sizes for large dimension VQ's, we use hierarchical structures to quantize the vector successively in stages. Since both the encoder and decoder are implemented by table lookups, there are no arithmetic computations required in the final system implementation. The algorithms are a novel combination of any generic Block transform (DCT, Haar, WHT) and hierarchical vector quantization. They use perceptual weighting and subjective distortion measures in the design of VQ's. They are unique in that both the encoder and the decoder are implemented with only table lookups and are amenable to efficient software and hardware solutions.

  • Data Compression Conference - Hierarchical vector quantization of perceptually weighted Block Transforms
    Proceedings DCC '95 Data Compression Conference, 1
    Co-Authors: N Chaddha, Mohan Vishwanath, Philip A Chou
    Abstract:

    This paper presents techniques for the design of generic Block transform based vector quantizer encoders implemented by table lookups. In these table lookup encoders, input vectors to the encoders are used directly as addresses in code tables to choose the codewords. There is no need to perform the forward or reverse Transforms. They are implemented in the tables. In order to preserve manageable table sizes for large dimension VQ's, we use hierarchical structures to quantize the vector successively in stages. Since both the encoder and decoder are implemented by table lookups, there are no arithmetic computations required in the final system implementation. The algorithms are a novel combination of any generic Block transform (DCT, Haar, WHT) and hierarchical vector quantization. They use perceptual weighting and subjective distortion measures in the design of VQ's. They are unique in that both the encoder and the decoder are implemented with only table lookups and are amenable to efficient software and hardware solutions.

G. Charith K. Abhayaratne - One of the best experts on this subject based on the ideXlab platform.

  • reversible integer to integer mapping of n point orthonormal Block Transforms
    Signal Processing, 2007
    Co-Authors: G. Charith K. Abhayaratne
    Abstract:

    Reversible integer-to-integer (I2I) mapping of orthonormal Transforms are vital for developing lossless coding with scalable decoding functionalities. A general framework for reversible I2I mapping of N-point, where N is a positive integer power of 2, orthonormal Block Transforms using recursive factorization of such transform matrices and the lifting scheme is presented. Designs include the discrete cosine transform (DCT) that maps integers to integers (I2I-DCT), the discrete sine transform that maps integers to integers (I2I-DST) and the Walsh-Hadamard transform that maps integer to integers (I2I-WHT). The main significant feature of these designs is that the transform coefficients are normalized according to the conventional scaling factors, which is vital for embedded coding, while preserving the integer-to-integer mapping and perfect reconstruction. This makes these Transforms usable in both lossless and lossy image coding, especially in scalable lossless coding. These generic N-point design of the above Transforms enables evaluating the effect of Block sizes of such Transforms in lossless coding. The performance is evaluated in terms of lossless image and video coding, quality scalable decoding, complexity and lifting step rounding effects.

  • VCIP - Orthonormal integer Block Transforms for lossless coding: design and performance analysis
    Visual Communications and Image Processing 2003, 2003
    Co-Authors: G. Charith K. Abhayaratne
    Abstract:

    In this paper a general framework for N-point, where N is any positive integer power of 2, orthonormal Block Transforms that map integers to integers using the lifting scheme is presented. The design of the Discrete Cosine Transform (DCT) that maps integers to integers (I2I-DCT), the Discrete Sine Transform that maps integers to integers (I2I-DST) and the Walsh Hadamard Transform that maps integer to integers (I2I-WHT) is presented. The main significance of this design is that the orthonormal property of the Transforms is maintained by proper normalisation while preserving the integer to integer mapping and perfect reconstruction. This makes these Transforms usable in both lossless and lossy image coding, especially in scalable lossless coding. The coding performance of these Transforms is evaluated in lossless image coding and lossless video coding applications.