• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.1
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• pp.161-169
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• 1996

This paper presents a new search region prediction method using vector quantization for the motion estimation. We find motion vectors using the full search BMA from two successive frame images first. Then the motion vectors are used for training a codebook. The trained codebook is the predicted search region. We used the unsupervised neural network for VQ encoding and codebook design. A major advantage of formulating VQ as neural networks is that the large number of adaptive training algorithm that are used for neural networks can be applied to VQ. The proposed method reduces the computation and reduce the bits required to represent the motion vectors because of the smaller search points. The computer simulation results show the increased PSNR as compared with the other block matching algorithms.

• The KIPS Transactions:PartB
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• v.10B no.6
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• pp.673-680
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• 2003

In this paper, we study the enhancement of VQ (Vector Quantization) design for text independent speaker recognition. In a concrete way, we present a non-iterative method which makes a vector quantization codebook and this method performs non-iterative learning so that the computational complexity is epochally reduced The proposed Classified Space VQ (CSVQ) design method for text Independent speaker recognition is generalized from Semi-noniterative VQ design method for text dependent speaker recognition. CSVQ contrasts with the existing desiEn method which uses the iterative learninE algorithm for every traininE speaker. The characteristics of a CSVQ design is as follows. First, the proposed method performs the non-iterative learning by using a Classified Space Codebook. Second, a quantization region of each speaker is equivalent for the quantization region of a Classified Space Codebook. And the quantization point of each speaker is the optimal point for the statistical distribution of each speaker in a quantization region of a Classified Space Codebook. Third, Classified Space Codebook (CSC) is constructed through Sample Vector Formation Method (CSVQ1, 2) and Hyper-Lattice Formation Method (CSVQ 3). In the numerical experiment, we use the 12th met-cepstrum feature vectors of 10 speakers and compare it with the existing method, changing the codebook size from 16 to 128 for each Classified Space Codebook. The recognition rate of the proposed method is 100% for CSVQ1, 2. It is equal to the recognition rate of the existing method. Therefore the proposed CSVQ design method is, reducing computational complexity and maintaining the recognition rate, new alternative proposal and CSVQ with CSC can be applied to a general purpose recognition.

• Journal of the Institute of Convergence Signal Processing
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• v.5 no.2
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• pp.91-95
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• 2004

In this paper, we propose a fuzzy controller for the evaluation of the quantization parameters in the H.263 coder. Our method adopts the Mamdani method for fuzzification and adopts the centroid method for defuzzification respectively. The inputs are variance, entropy in the spatial domain, current motion vector and previous motion vector in the temporal. Fuzzy variables are determined to be compatible in visual characteristics and fuzzy membership function is induced and then, FAM banks are designed to reduce the number of rules. In this paper, fuzzy quantization has been applied to a practical video compression. This results show that the quality of decode image enhances and the rate control method using fuzzy quantization is effective.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.60-69
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• 1998

This paper proposes a speech synthesis method using Fuzzy VQ, and then study how to make choice of fuzziness value which optimizes (controls) the performance of FVQ in order to obtain the synthesized speech which is closer to the original speech. When FVQ is used to synthesize a speech, analysis stage generates membership function values which represents the degree to which an input speech pattern matches each speech patterns in codebook, and synthesis stage reproduces a synthesized speech, using membership function values which is obtained in analysis stage, fuzziness value, and fuzzy-c-means operation. By comparsion of the performance of the FVQ and VQ synthesizer with simmulation, we show that, although the FVQ codebook size is half of a VQ codebook size, the performance of FVQ is almost equal to that of VQ. This results imply that, when Fuzzy VQ is used to obtain the same performance with that of VQ in speech synthesis, we can reduce by half of memory size at a codebook storage. And then we have found that, for the optimized FVQ with maximum SQNR in synthesized speech, the fuzziness value should be small when the variance of analysis frame is relatively large, while fuzziness value should be large, when it is small. As a results of comparsion of the speeches synthesized by VQ and FVQ in their spectrogram of frequency domain, we have found that spectrum bands(formant frequency and pitch frequency) of FVQ synthesized speech are closer to the original speech than those using VQ.

• The Journal of the Acoustical Society of Korea
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• v.20 no.4
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• pp.29-34
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• 2001

In this paper, we designed an LSF coefficient quantizer of the wideband speech codec that can produce high quality speech service. For the efficient LSF coefficient quantizer, the interframe correlation was used. Also we separately quantized the LSF coefficients with high and low interframe correlation. Predictive pyramid vector quantizer (PVQ) was used for quantizing the LSF coefficients with high interframe correlation, and PVQ was used for quantizing the LSF coefficients with low interframe correlation. Experiments show that the proposed UF quantizer can quantize LSF information in 40 bits/frame, with an average spectral distortion (SD) of 1 dB and less than 3.87% frames having SD greater than 2 dB.

• Proceedings of the Korean Institute of Communication Sciences Conference
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• 1992.10a
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• pp.302-305
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• 1992

• Journal of KIISE:Software and Applications
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• v.27 no.4
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• pp.422-431
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• 2000

This paper proposes a new codebook generation method, called a PCA-Based VQ, that incorporates the PCA (Principal Component Analysis) technique into VQ (Vector Quantization) codebook design. The PCA technique reduces the data dimensions by transforming input image vectors into the feature vectors. The cluster of feature vectors in the transformed domain is bisectioned into two subclusters by an optimally chosen partitioning hyperplane. We expedite the searching of the optimal partitioning hyperplane that is the most time consuming process by considering that (1) the optimal partitioning hyperplane is perpendicular to the first principal axis of the feature vectors, (2) it is located on the equilibrium point of the left and right cluster's distortions, and (3) the left and right cluster's distortions can be adjusted incrementally. This principal axis bisectioning is successively performed on the cluster whose difference of distortion between before and after bisection is the maximum among the existing clusters until the total distortion of clusters becomes as small as the desired level. Simulation results show that the proposed PCA-based VQ method is promising because its reconstruction performance is as good as that of the SOFM (Self-Organizing Feature Maps) method and its codebook generation is as fast as that of the K-means method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2001.10a
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• pp.579-582
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• 2001

Vector Transformation is a new method unified vector quantization and coding. So far, codebook generation applied to coding was LBG algorithm. But using the advantage of SOFM(Self-Organizing Feature Map) based on neural network can improve a system's performance. In this paper, we generated VTC(Vector Transformation Coding) codebook applied with SOFM algorithm and compare the result for several coding rates with LBG algorithm. The problem of Vector quantization is complicated calculation and codebook generation. So, to solve this problem, we used neural network approach method.

• Proceedings of the Acoustical Society of Korea Conference
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• 1995.06a
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• pp.164-167
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• 1995

RPE 음성부호화기에서 합성 필터로 인한 구동벡터 양자화잡음의 증폭효과를 분석하고 regular pulse 시퀀스의 양자화로 인한 성능감쇄를 줄이기 위해 pyramid vector 양자화방식을 도입하였다. 제안된 방식의 성능평가는 구동시퀀스 양자화를 위해 adaptive PCM을 이용하는 GSM 표준 RPE 방식과의 객관적 및 주관적 성능비교를 통해 수행하였다.T JDSMDQLRY 결과 제안된 방식은 대략 1dB의 SNR 및 segmental SNR 값 증가를 가져왔고, 또한 비공식 청취시험결과 명료도의 증가를 느낄 수 있었다.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.4
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• pp.38-44
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• 1999

본 논문에서는 웨이브릿 변환과 선택적 예측 벡터양자화를 이용한 인공위성 화상데이타 부호화 방법을 제안하였다. 이 방법에서는 대역내 중복성을 제거하기 위하여 각각의 대역을 웨이브릿 변환하고, 대역간 중복성을 제거하기 위해 에측하는 대역으로부터 생성된 임계치 지도를 이용하여 선택적 예측 벡터양자화를 행한다. 따라서 이 방법은 대역내 및 대역간 중복성을 효과적으로 제거하기 때문에 부호화 효율을 향상시킨다. 이 방법을 실제 Landsat TM 인공위성 화상데이타에 실험한 결과 기존의 방법에 비하여 부호화 효율이 향상됨을 확인하였다.