Asymptotically Optimal Distribution Preserving Quantization for Stationary Gaussian Processes

Distribution preserving quantization (DPQ) has been proposed as a lossy coding tool that yieldssuperior quality over conventional quantization, when applied to perceptually relevant signals. DPQ ai ...

[1]  W. Bastiaan Kleijn,et al.  Quantization with Constrained Relative Entropy and Its Application to Audio Coding , 2009 .

[2]  Tamás Linder,et al.  High-Resolution Source Coding for Non-Difference Distortion Measures: Multidimensional Companding , 1999, IEEE Trans. Inf. Theory.

[3]  Yuval Kochman,et al.  Achieving the Gaussian Rate–Distortion Function by Prediction , 2007, IEEE Transactions on Information Theory.

[4]  Thomas M. Cover,et al.  Elements of Information Theory , 2005 .

[5]  RECOMMENDATION ITU-R BS.1534-1 - Method for the subjective assessment of intermediate quality level of coding systems , 2003 .

[6]  G. G. Stokes "J." , 1890, The New Yale Book of Quotations.

[7]  Roch Lefebvre,et al.  The adaptive multirate wideband speech codec (AMR-WB) , 2002, IEEE Trans. Speech Audio Process..

[8]  Meir Feder,et al.  On lattice quantization noise , 1996, IEEE Trans. Inf. Theory.

[9]  W.B. Kleijn,et al.  Flexible Quantization of Audio and Speech based on the Autoregressive Model , 2007, 2007 Conference Record of the Forty-First Asilomar Conference on Signals, Systems and Computers.

[10]  Robert M. Gray,et al.  Toeplitz and Circulant Matrices: A Review , 2005, Found. Trends Commun. Inf. Theory.

[11]  Meir Feder,et al.  Information rates of pre/post-filtered dithered quantizers , 1993, IEEE Trans. Inf. Theory.

[12]  W. Bastiaan Kleijn,et al.  Distribution Preserving Quantization With Dithering and Transformation , 2010, IEEE Signal Processing Letters.

[13]  Ian H. Witten,et al.  Arithmetic coding for data compression , 1987, CACM.

[14]  Judea Pearl,et al.  On coding and filtering stationary signals by discrete Fourier transforms (Corresp.) , 1973, IEEE Trans. Inf. Theory.

[15]  W. Kleijn,et al.  Enhancement of coded speech by constrained optimization , 2002, Speech Coding, 2002, IEEE Workshop Proceedings..

[16]  Toby Berger,et al.  Rate distortion theory : a mathematical basis for data compression , 1971 .

[17]  Sae-Young Chung,et al.  Sphere-bound-achieving coset codes and multilevel coset codes , 2000, IEEE Trans. Inf. Theory.

[18]  Meir Feder,et al.  On universal quantization by randomized uniform/lattice quantizers , 1992, IEEE Trans. Inf. Theory.

[19]  Richard A. Davis,et al.  Time Series: Theory and Methods , 2013 .

[20]  Richard A. Davis,et al.  Time Series: Theory and Methods (2nd ed.). , 1992 .

[21]  Bernd Edler,et al.  Audio coding using a psychoacoustic pre- and post-filter , 2000, 2000 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.00CH37100).

[22]  Edward J. Delp,et al.  Moment preserving quantization [signal processing] , 1991, IEEE Trans. Commun..

[23]  Hideki Kawahara,et al.  YIN, a fundamental frequency estimator for speech and music. , 2002, The Journal of the Acoustical Society of America.

[24]  A. Tversky Features of Similarity , 1977 .

[25]  M. Rosenblatt Remarks on a Multivariate Transformation , 1952 .

[26]  Robert M. Gray,et al.  Toeplitz And Circulant Matrices: A Review (Foundations and Trends(R) in Communications and Information Theory) , 2006 .

[27]  Simon Litsyn,et al.  Lattices which are good for (almost) everything , 2005, IEEE Transactions on Information Theory.

[28]  Minyue Li,et al.  Distribution Preserving Quantization , 2011, ArXiv.

[29]  Robert J. Safranek,et al.  Signal compression based on models of human perception , 1993, Proc. IEEE.