Entropy constrained scalar quantizer for a Laplace-Markov...

Details Entropy constrained scalar quantizer for a Laplace-Markov... Entropy constrained scalar quantizer for a Laplace-Markov...

2006-12-05

2006-12-05

Rao, Anand (Department: 2613)

Pulse or digital communications

Bandwidth reduction or expansion

Television or motion video signal

C375S240050, C375S240080

Reexamination Certificate

active

07145948

ABSTRACT:
A video coding system and method for coding an input frame in which the evolution of discrete cosine transform (DCT) coefficients is modeled as a Laplace-Markov process, the system comprising: a base layer processing system for generating a base layer reconstruction; an enhancement layer processing system for generating an enhancement layer reconstruction; and an entropy constrained scalar quantizer (ECSQ) system for descritizing a prediction residual between the input frame and an estimation theoretic (ET) prediction output; wherein the ECSQ system utilizes an ECSQ that comprises a uniform threshold quantizer with a deadzone size defined by the equation:Γ⁡(α,t*)=2⁢(11-ρ2⁢ⅇt*-1),where⁢⁢Γ⁡(α,β)=(ⅇα-1)⁢exp⁢{-α⁡[d⁡(α-δ⁡(α))-d⁡(-β)d⁡(α-δ⁡(α))-d⁡(-δ⁡(α))]}⁢.

REFERENCES:
patent: 6731811 (2004-05-01), Rose
On the structure of optimal entropy-constrained scalar quantizers Gyorgy, A.; Linder, T.; IEEE Transactions on , vol.: 4 , Issue: 2, Feb. 2002 pp.: 416-427.
Optimal entropy constrained scalar quantization for exponential and Laplacian random variables Sullivan, G.J.;Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on , vol. v, Apr. 19-22, 1994 p. 265-268.
“Toward Optimality in Scalable Predictive Coding”, by Rose et al, IEEE Transactions on Image Processing, vol. 10, No. 7, Jul. 2001, pp. 965-976.
“Efficient Scalar Quantization of Exponential and Laplacian Random Variables” by Sullivan, IEEE Transactions on Information Theory, vol. 42, No. 5, Sep. 1996, pp. 1365-1374.
K. Rose et al; “Toward Optimality in Scalable Predictive Coding”, IEEE Transactions on Image Processing, vol. 10, No. 7, Jul. 200L.
G. Sullivan, “Efficient Scalar Quantization of Exponential and Laplacian Random Variables”, IEEE Transactions on Information Theory, vol. 42, No. 5, Sep. 1996.

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