• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 제13회 신호처리 합동 학술대회 논문집
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• pp.667-670
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• 2000

This paper provides a heuristic theory for modeling and analysis of vector quantization effects in 2-dimensional subband filter banks. This model is used as the basis for optimal filter bank design. The scalar non-linear gain-plus-additive noise quantization model can be used to represent each vector quantizer in 2-band subband codec. The validity and accuracy and of this analytic model is confirmed by comparing the calculated model quantization errors with actual simulation of the optimum LBG vector quantizer. Numerical design examples for the optimum separable paraunitary filter banks are suggested in this paper.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(II)
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• pp.1422-1426
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• 1987

In this paper, an adaptive DPCM scheme is presented for encoding monochrome images with easy hardware implementation at a transmission rate of exactly 1 bit/pel. The system is mainly composed of a compensated mean predictor and an adaptive two-level quantizer with backward estimation. In this system, the predictor is a sort of two-dimensional ARMA predictor in which a moving-average part is added to the conventional mean predictor. The quantizer adapts to the local statistics of its input without overhead information. To reduce annoying granular noise in the reconstructed image, Lee filter is used after reconstruction in the receiver.

• Journal of information and communication convergence engineering
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• 제13권3호
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• pp.152-158
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• 2015

We consider the problem of designing independently operating local quantizers at nodes in distributed estimation systems, where many spatially distributed sensor nodes measure a parameter of interest, quantize these measurements, and send the quantized data to a fusion node, which conducts the parameter estimation. Motivated by the discussion that the estimation accuracy can be improved by using the quantized data with a high probability of occurrence, we propose an iterative algorithm with a simple design rule that produces quantizers by searching boundary values with an increased likelihood. We prove that this design rule generates a considerably reduced interval for finding the next boundary values, yielding a low design complexity. We demonstrate through extensive simulations that the proposed algorithm achieves a significant performance gain with respect to traditional quantizer designs. A comparison with the recently published novel algorithms further illustrates the benefit of the proposed technique in terms of performance and design complexity.

• 대한전자공학회논문지
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• 제26권8호
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• pp.1227-1237
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• 1989

In this paper, we propose a lossless progressive image transmission scheme using hierarchical pyramid structure and classified vector quantizer in DCT domain. By adopting DCT to the hierarchical pyramid signals, we can reduce the spatial redundance. Moreover, the DCT coefficients can be encoded efficiently by using classified vector quantizer in DCT domain. The classifier is simply based on the variance of a subblock. Also, the mirror set of training set of images can improve the robustness of codebooks. Progressive image transmission can be achieved through following processes: from top to bottom level of planes in a pyramid, and from high to low AC variance class in a plane. Some simulation results with real images show that the proposed coding scheme yields a good performance at below 0.3 bpp and an excellent result at 0.409 bpp. The proposed coding scheme is well suited for lossless progressive image transmission as well as image data compression.

• 전자공학회논문지B
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• 제31B권10호
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• pp.130-139
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• 1994

Video compression algorithms are based on removing spatial and/or temproal redundancy inherent in image sequences by predictive(DPCM) encoding, transform encoding, or a combination of predictive and transform encoding. In this paper, each 8$\times$8 DCT coefficient of DFD(displaced frame difference) is adaptively quantized by one of the four quantizers depending on total distortion level, which is determined by characteristics of HVS(human visual system) and buffer status. Therefore, the number of possible quantizer selection vectors(patterns) is 4$^{64}$. If this vectors are coded, toomany bits are required. Thus, the quantizer selection vectors are limited to 2048 for Y and 512 for each U, V by the proposed method using SWAD(sum of weighted absolute difference) for discriminating vectors. The computer simulation results, using the codebook vectors which are made by the proposed method, show that the subjective and objective image quality (PSNR) are goor with the limited bit allocation. (17Mbps)

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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• pp.2184-2187
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• 2003

Quantizers for digital coding systems are usually optimized with respect to a model of the probability density function of the random variable to be quantized. Thus a mismatch of the quantizer relative to the actual statistics of the random variable may be unavoidable. This paper presents the results of an experimental investigation of mismatched quantizers. For the modeling of the source statistics, various types of the Weibull distribution are used, and the optimization of the quantizer is carried with respect to the minimum mean-square error (mse) criterion. The goal of this paper is to find an estimate formula for the mismatched quantizer on Weibull sources.

• 전자공학회논문지S
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• 제34S권4호
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• pp.50-56
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• 1997

In this paper, efficient quantization methods of line spectrum pairs (LSP) which has good performances and low complexity and memory are proosed for vocoder of mobile communication system. The adaptive quantization method utilizing the ordering property of LSP parameters is used in a scalar quantizer and a vector-scalar hybrid quantizer. The proposed scalar quantization algorithm needs 31 bits/frame to maintain the transparent quality of speech. The improved vector-scalar quantizer achieves an average spectral distortion of 1dB using 26 bits/frame. The proposed methods are evaluated in the channel errors and changed the predictor structure to maintain the robustness to channel errors.

• 한국통신학회논문지
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• 제25권1A호
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• pp.48-55
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• 2000

본 논문에서는 모의 실험을 통하여, 데이터의 분포가 Gauss 분포, 균등 분포 등의 경우, 어느 한 구간이 다른 구간에 비하여 확률도 크고 구간내의 오차도 크다면 이는 최적 양자화가 아니다라는 가정을 하였다. 이 가정을 LBG 알고리즘에 추가하여 수정된 LBG 알고리즘을 만들고, 이 알고리즘의 성능을 측정하였다. 수정된 알고리즘에 의한 코드 북의 오차는 본래의 알고리즘에 비하여 오차의 크기도 감소하였고, 오차의 편차도 감소하였다.

• 한국통신학회논문지
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• 제36권6C호
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• pp.384-390
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• 2011

The paper derives formulas for the mean-squared error distortion and resulting signal-to-noise (SNR) ratio of a fixed-rate scalar quantizer designed optimally in the minimum mean-squared error sense for a Gaussian density with the standard deviation ${\sigma}_q$ when it is mismatched to a Laplacian density with the standard deviation ${\sigma}_q$. The SNR formulas, based on the key parameter and Bennett's integral, are found accurate for a wide range of $p\({\equiv}\frac{\sigma_p}{\sigma_q}\){\geqq}0.25$. Also an upper bound to the SNR is derived, which becomes tighter with increasing rate R and indicates that the SNR behaves asymptotically as $\frac{20\sqrt{3{\ln}2}}{{\rho}{\ln}10}\;{\sqrt{R}}$ dB.

• 전자공학회논문지B
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• 제28B권5호
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• pp.318-326
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• 1991

A Quantizer reconstruction level control method for block artifact reduction in DCT image coding is described. In our scheme, quantizer reconstruction level control is obtained by adding quantization level step size to the optimum quantization level in the direction of reducing the block artifact by minimizing the mean square error(MSE) and error difference(EDF) distribution in boundary without the other additional bits. In simulation results, although the performance in terms of signal to noise ratio is degraded by a little amount, mean square of error difference at block boundary and mean square error having relation block artifact is greatly reduced. Subjective image qualities are improved compared with other block artifact reduction method such as postprocessing by filtering and trasform coding by block overlapping. But the addition calculations of 1-dimensional DCT become to be more necessary to coding process for determining the reconstruction level.