• The Journal of the Acoustical Society of Korea
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• v.23 no.4
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• pp.333-339
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• 2004

This Paper proposes the vector quantizer-pyramid vector quantizer(VQ-PVQ) structure. Also both predictive structure and safety-net concept are combined into the VQ-PVQ to quantize the IPC parameter of wideband speech codec. The Performance is compared to the LPC vector quantizer used in the AMR-WB(ITU-T G.722.2). demonstrating reduction in both spectral distortion and encoding memory.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.21 no.2
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• pp.333-339
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• 1996

In this paper, an effiicent quatization method of line spectrum pairs(LSP) with cascaded structure of vector quantizer and scalar quantizer is proposed. First, input LSP parameters is vector-quantized using a codebook with a moderate number of entries. In the second stage of quantization, the components of residual vector are individution improve the quantizer by the scalar quantizer. The utilization of ordering property and the inclusion of interframe prediction improve the quantizer performance and remove the stability check routine. The new vector-scalar cascaded quantizer using 27 bits/frame shows a transparent quality that an average specytural distortion is 1 dB and the frame proportion with above 2 dB spectral distion is less than 2%.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.1362-1364
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• 1996

In this paper a Dear lossless compression of medical images with vector quantizer is proposed. In order to apply the vector quantizer to medical images, the peak error in the reconstructed image is reduced down to 1. Simulation results show that the proposed coding scheme provides better performance with a PSNR improvement compared to the conventional JPEG standard.

• The Journal of the Acoustical Society of Korea
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• v.17 no.4E
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• pp.35-40
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• 1998

In this paper, an efficient quantization method of line spectrum pairs(LSP) with cascaded structure of vector quantizer and scalar quantizer is proposed. First, input LSP parameters is vector-quantized using a codebook a with a moderate number of entries. In the second stage of quantization, the components of residual vector are individually quantized by the scalar quantizer. The utilization of ordering property of LSP parameters and the inclusion of interframe prediction improve the quantizer performance and remove the stability check routine after quantization procedure. The new vector-scalar hybrid quantizer using 26 bits/frame shows a transparent quality of speech that an average spectral distortion is 1 dB and the frame proportion with above 2 dB spectral distortion is less than 2%. The performances of proposed quantization method is evaluated in the transmission errors.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.40 no.4
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• pp.286-291
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• 2003

In this Paper, we designed an LSP(Line Spectral Pairs) parameter quantizer with cascaded structure of vector quantizer and scalar quantizer for the wideband speech coder. We have chosen the 16th-order of the LP coefficients. These coefficients are then transformed into the LSP parameters which have the excellent properties for quantization and easy stability checking condition of synthesis filter. In the first stage of quantization, input LSP parameters are split-vector-quantized using two 8-th order codebooks. In the second stage, the components of residual vector are individually quantized by the scalar quantizer utilizing the ordering property of LSP parameters. The designed adaptive VQ-SQ quantizer using 35 bits/frame shows the wideband transparency that the average spectral distortion should be less than 1.6 ㏈ and less than 4% of the frames should have SD above 3 ㏈. The simulation results show that the designed quantizer provides a 2-3 bits/frame saving over the typical vector-scalar quantizer.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.6
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• pp.127-136
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• 1998

This paper proposes a new MVQMultistage Vector Quantizer) using a hybrid structure. While in a conventional MVQ, the quantizers of all stages perform the encoding procedure for input signals, we introduce a quantizer that performs selectively. The proposed quantizer with a hybrid structure is composed of a FSVQ(Finite-State Vector Quantizer) for the first stage and a ordinary VQ(Vector Quantizer) for the second stage. A input block is firstly encoded by the FSVQ of the first stage. If the Euclidean distortion measure between original signals and the codevector selected from the state codebook of the FSVQ is less than a prespecified value, only the FSVQ is used for image coding. Otherwise, both the FSVQ of the first stage and the ordinary VQ of the second stage are used for image coding. While the conventional MVQ has an advantage that can achieve low encoding complexity in comparison to the ordinary VQ, but has a disadvantage that is suboptimal with respect to the performance measure and can not achieve the bit rate reduction, the proposed method achieve not only the bit rate reduction but also the performance improvement.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.6
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• pp.672-679
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• 1988

In this paper, attempts have been made to code images employing a separating mean vector quantizer(SMVQ). Then we analyzed the performance of the SMVQ experimentally as well as analytically. The results of simulation with natural images are presented. But, conclusively the performance of the SMVQ technique is not better than that of the conventional vector quantizer. In this paper, a brief analysis in which we revealed that the performance, based on the mean square error measure, of the SMVQ is not favorable is favorable is discussed.

• The Transactions of the Korea Information Processing Society
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• v.7 no.2
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• pp.529-535
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• 2000

In this paper, we propose a new method of designing the vector quantizer which is robustness to coding results and independent of statistical characteristics of an input image in wavelet transformed image coding processes. The most critical drawback of a conventional vector quantizer is the degradation of coding capability resulted from the discordance between quantizer objective image and statistical characteristics of training sequence which is for generating representing vector. In order to resolve the problem of conventional methods, we use independent random-variables and pseudo image to which image correlation and edge component were added, as a training sequence for generating representing vector. We have done a computer simulation in order to compare coding capability between a vector quantizer designed by the proposed method and one with the conventional method using real image as same as that is objective to coding of training sequence used in codebook generation. The results show the superiority of the proposed vector quantizer method at the aspect of coding capability compared to conventional one. They also clarify the problems of conventional methods.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.1
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• pp.107-113
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• 2017

This paper provides a new approach for modeling of vector quantizer(VQ) followed by analysis and design of subband codecs with imbedded VQ's. We compute the mean squared reconstruction error(MSE) which depend on N the number of entries in each codebook, k the length of each codeword, and on the filter bank(FB) coefficients in subband codecs. We show that the optimum M-band filter bank structure in presence of pdf-optimized vector quantizer can be designed by a suitable choice of equivalent scalar quantizer parameters. Specific design examples have been developed for two different classes of filter banks, paraunitary and the biorthogonal FB and the 2 channel case. These theoretical results are confirmed by Monte Carlo simulation.

• Convergence Security Journal
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• v.6 no.4
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• pp.83-90
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• 2006

In this paper, we propose a new design method for a robust vector quantizer that is independent of the statistical characteristics of input images in the wavelet transformed image coding. The conventional vector quantizers have failed to get quality coding results because of the different statistical properties between the image to be quantized and the training sequence for a codebook of the vector quantizer. Therefore, in order to solve this problem, we used a pseudo image as a training sequence to generate a codebook of the vector quantizer; the pseudo image is created by adding correlation coefficient and edge components to uniformly distributed random numbers. We will clearly define the problem of the conventional vector quantizers, which use real images as a training sequence to generate a codebook used, by comparing the conventional methods with the proposed through computer simulation. Also, we will show the proposed vector quantizer yields better coding results.