Switched nonuniform polar quantization of sources with a wide dynamic range of power

Perić, Zoran; Jovanović, Aleksandra; Stefanović, Mihajlo; Bogosavljevic, S.M.

doi:10.1134/s1064226907120066

Cited by 6 publications

(19 citation statements)

References 8 publications

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“…These facts explain why in Ref. [18] the constant SQNR is not sustained over broad variance range. Namely, in that paper the high dynamic range polar quantization was performed utilizing the same compression function, but the code vectors number per amplitude level was optimized and both, compression parameter and dimension were small.…”

Section: Introductionmentioning

confidence: 79%

“…Total distortion D of proposed vector quantizer can be found as sum of granular distortion D g given with (16) and overload distortion D o [7,17,18] defined with…”

Section: Distortion For Geometric Vq With A-law Radial Compression Fumentioning

confidence: 99%

“…Namely, in that paper the high dynamic range polar quantization was performed utilizing the same compression function, but the code vectors number per amplitude level was optimized and both, compression parameter and dimension were small. The narrower dynamic range of log-polar quantization in comparison with optimal polar quantization [18] caused that later investigations [19,20] were not toward to high dimensional logarithmic quantization. To achieve quality improvement during high dynamic range quantization, adaptive technique was combined with log-scalar quantization for which optimal compression parameter is found in respect to maximal SQNR [19,20].…”

Section: Introductionmentioning

confidence: 99%

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Radial compression function for vector quantizer of Laplacian source with high dynamic variance range

Perić

Jovanović

2010

Trans Emerging Tel Tech

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In this paper, our aim is to define a high dynamic range vector quantization model for an i.i.d. Laplacian source. In order to do this we use a geometric approach and lattice quantization. As a result, we achieve symmetry in distribution of code vectors and introduce the radial scalar compression function for lattice cell side determination. This enables derivation of a sophisticated creation for a condition which the radial compression function should satisfy in order to make the SQNR nondependent on variance. It is interesting that the obtained solution represents the generalisation of solution in the case of high dynamic range scalar quantization. Because of that, in the second part of the paper, the well-known semilogarithmic A-law compression characteristic is utilized as radial scalar compression function of geometric vector quantizer. It is shown that such a model has very good performances over a very wide variance range. The proper choice of compression parameter A and dimension n enables the constant SQNR to sustain over much wider variance range than in case of log-scalar quantization. Particularly, the high dimension makes it possible to broaden the variance range over which SQNR remains constant by increasing the A value simultaneously holding the SQNR level unchanged. In comparison with the widely used log-scalar quantization, the presented solution for dimensions from 10 to 140 gives a quality improvement of 7--9 dB, while comparison of maximal SQNR value to that of optimal scalar quantization shows the SQNR growth of 3--5 dB. Furthermore, for dimension 40 the SQNR maximum is only for 0.5 dB lower than that of optimal vector quantization, while dynamic range characteristic broadening is considerable. The cited benefits of high dynamic range vector quantization make it possible to realize a high quality signal compression. Besides, in comparison with the adaptive quantization, our proposal has a smaller implementation complexity.

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Section: Introductionmentioning

confidence: 79%

“…Total distortion D of proposed vector quantizer can be found as sum of granular distortion D g given with (16) and overload distortion D o [7,17,18] defined with…”

Section: Distortion For Geometric Vq With A-law Radial Compression Fumentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Radial compression function for vector quantizer of Laplacian source with high dynamic variance range

Perić

Jovanović

2010

Trans Emerging Tel Tech

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“…Quantizers obtained using companding technique are called companding quantizers. This technique is applicable for various types of quantizers, see for example (Gersho and Gray, 1992;Jayant and Noll, 1984;Perić et al, 2007;Swaszek and Ku, 1986). An companding polar quantizer…”

Section: Initial Valuesmentioning

confidence: 99%

“…There are also models in which reconstruction and decision magnitude levels are not uniformly distributed i.e. nonuniform polar quantizers (Perić et al, 2007;Swaszek and Ku, 1986;Swaszek and Thomas, 1983). It should be also emphasized that Wilson (Wilson 1980) first defined the unrestricted polar quantizers, i.e.…”

Section: Introductionmentioning

confidence: 99%

An iterative method for optimal resolution‐constrained polar quantizer design

Petković

Perić

Jovanović

2011

COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering

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This paper addresses the problem of polar quantization optimization. Particularly, the aim of this investigation is to find the method for the optimal resolution-constrained polar quantizer design.The new iterative algorithm for determination of the optimal decision and representation magnitude levels and algorithm for optimization of number of phase cells within each magnitude level, is proposed.At high rates, the new optimal polar quantizer outperforms the optimal polar compander for 0.2dB, while the more significant gain should be expected at lower rates. In this paper, in order to enable practical implementation of quantizer model, algorithm which transforms real values for the optimal numbers of phase cells within magnitude levels into integer ones is also proposed. Moreover, the approximate closed form of signal to quantization ratio (SQNR) is derived.Since circularly symmetric sources and complex presentation of signals arise in numerous applications, it can be concluded that the usage area of the suggested proposal is very wide (audio coding, image coding, spectral phase coding SPC, synthetic aperture radars systems SARs, coding of the discrete Fourier transform).It should be emphasized that in contrast to earlier work, where models have been designed under high-rate assumption, the obtained nonuniform unrestricted polar quantizer is optimal for all rates.

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