• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.7
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• pp.107-115
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• 1996

The average distortio of the vector quantizer is calcualted using a probability function F of the input source for a given codebook. But, since the input source is unknown in geneal, using the sample vectors that is realized from a random vector having probability function F, a time-average opeation is employed so as to obtain an approximation of the average distortion. In this case the size of the smple set should be large so that the sample vectors represent true F reliably. The theoretical inspection about the approximation, however, is not perfomed rigorously. Thus one might use the time-average distortion without any verification of the approximation. In this paper, the convergence characteristics of the time-average distortions are theoretically investigated when the size of sample vectors or the size of codebook gets large. It has been revealed that if codebook size is large enough, then small sample set is enough to obtain the average distortion by approximatio of the calculated tiem-averaged distortion. Experimental results on synthetic data, which are supporting the analysis, are also provided and discussed.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.42-49
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• 1996

In this paper, we propose a satellite multispectral image data compression method using classified vector quantization. This method classifies each pixel vector considering band characteristics of multispectral images. For each class, we perform both intraband and interband vector quantization to romove spatial and spectral redundancy, respectively. And residual vector quantization for error images is performed to reduce error of interband vector quantization. Thus, this method improves compression efficiency because of removing both intraband(spatial) and interband (spectral) redundancy in multispectral images, effectively. Experiments on landsat TM multispectral image show that compression efficiency of proposed method is better than that of conventional method.

• Proceedings of the IEEK Conference
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• 2006.06a
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• pp.343-344
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• 2006

In this paper, the biomedical signal compression method with multi-stage vector quantization is proposed. It utilizes characteristic of wavelet coefficients in which the energy is concentrated on approximation coefficients. The transmitted codebook index consists code vectors obtained by wavelet coefficients of ECG and Error signals from the 1024 block length, respectively. The proposed compression method showed 2.1298% in average PRD and 1.8 kbits/sec in CDR.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.11
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• pp.153-162
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• 1995

When vector quantization is used in low rate image coding (e.g., R<0.5), the primary problem is the tremendous computational complexity which is required to search the whole codebook to find the closest codevector to an input vector. Since the number of code vectors in a vector quantizer is given by an exponential function of the dimension. i.e., L=2$^{nR}$ where Rn. To alleviate this problem, a multiple shell structure of hypercube feature maps (MSSHFM) is proposed. A binary HFM of k-dimension is composed of nodes at hypercube vertices and a multiple shell architecture is constructed by surrounding the k-dimensional hfm with a (k+1)-dimensional HFM. Such a multiple shell construction of nodes inherently has a complete tree structure in it and an efficient partial search scheme can be applied with drastically reduced computational complexity, computer simulations of still image coding were conducted and the validity of the proposed method has been verified.

• Journal of the Korean Institute of Telematics and Electronics C
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• v.34C no.1
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• pp.42-50
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• 1997

Vector quantization has shown to be useful for compressing data related with a wide rnage of applications such as image processing, speech processing, and weather satellite. Neural networks of images this paper propses a efficient neural network learning algorithm, called learning count control algorithm based on the frquency sensitive learning algorithm. This algorithm can train a results more codewords can be assigned to the sensitive region of the human visual system and the quality of the reconstructed imate can be improved. We use a human visual systrem model that is a cascade of a nonlinear intensity mapping function and a modulation transfer function with a bandpass characteristic.

• 유체기계공업학회:학술대회논문집
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• 1999.12a
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• pp.317-323
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• 1999

The necessity of diagnosis of the rotating machinery which is widely used in the industry is increasing. Many research has been conducted to manipulate field vibration signal data for diagnosing the fault of designated machinery. As the pattern recognition tool of that signal, neural network which use usually back-propagation algorithm was used in the diagnosis of rotating machinery. In this paper, self-organizing feature map(SOFM) which is unsupervised learning algorithm is used in the abnormal vibration diagnosis of rotating machinery and then learning vector quantization(LVQ) which is supervised teaming algorithm is used to improve the quality of the classifier decision regions.

• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.538-540
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• 2000

본 논문에서는 적응적인 웨이블릿 변환에 기초한 저속 비트율 비디오 코딩 방법의 새로운 알고리즘을 제안한다. 접근 방법은 양자화된 웨이블릿 계수들이 웨이블릿 서브밴드 구조내에서 중복성을 활용하는 메커니즘에 의해서 전처리 된다면 코딩 절차가 더욱 효과적으로 나타난다. 그러므로 본 논문에서는 코딩부분의 최적화 활동에 초점을 맞추어 완전한 중복 블록 움직임 보상된 에어프레임에서 일치를 확보하기 위해 이용하고, 향상된 코사인 윈도우를 적용하였다. 또한 웨이블릿 변환은 각 일치한 움직임 보상된 에러 프레임을 전체적인 에너지 컴팩션에 도달하도록 적용된다. 움직임 벡터의 수평적, 수직적 컴포넌트는 적응적 산술적 코딩을 사용하여 독립적으로 인코드되는 반면에 의미있는 웨이블릿 계수는 적응적 산술 코딩을 사용함에 의해서 비트-플레인 순서로 인코드된다. 제안된 부호기는 28Kbits에서 PSNR이 평균적으로 각각 대략 2.07과 1.38dB에 존재하는 H.263과 ZTE를 초과한다. 전체순서 코딩에 대하여도 3DWCVC 방법은 평균적으로 각각 0.35와 0.71dB을 나타내는 H.263과 ZTE보다 우수한 성능을 보인다.

• The Transactions of the Korea Information Processing Society
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• v.7 no.3
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• pp.1013-1020
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• 2000

In this paper, we propose an algorithm which segments hierarchically blocks of image using discrete cosine transform(DCT) and execute finite-state vector quantization (FSVQ) for each block. Using DCT coefficient feature, image is segmented hierarchically to large smooth block and small edge block, then the block hierarchy informations are transmitted. The codebooks are respectively constructed for each hierarchical blocks, the encoder transmits codeword index using FSVQ for reducing encoded bit with hierarchical segmentation. Compared with side match VQ(SMVQ) and hierarchical FSVQ(HFSVQ) algorithm, about Zelda and Boat image, the new algorithm shows better picture quality with 1.97dB and 2.85 dB difference as to SMVQ, 1.78dB and 1.85dB diffences as to HFSVQ respectively.

• Proceedings of the Korea Information Processing Society Conference
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• 2002.11a
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• pp.7-10
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• 2002

본 논문에서는 MPEG-7의 활동도 기술자를 이용한 비디오 기술을 제안한다. 제안한 방법은 압축상태의 비디오 자료에서 직접 움직임 벡터들을 추출, 각 프레임들의 활동도의 강도를 계산하고 프레임의 흐름에 따라 계산된 활동도의 변화량에 대해 퓨리에 변환을 적용하여 얻어진 주파수 성분을 분석하여 활동도의 시간적 분포도를 계산한다. 계산된 강도 및 분포도는 MPEG-7의 표준에 따르기 위해 양자화하여 비디오 요약에 이용한다.

• Proceedings of the Korean Information Science Society Conference
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• 2005.07b
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• pp.889-891
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• 2005

디지털 기술과 통신 기술의 발전으로 멀티미디어 컨텐츠가 급격히 증가하고 있다. 이러한 멀티미디어 컨텐츠는 다양한 유무선 서비스 환경에서 실시간 서비스가 가능해야 한다. 그러기 위해서는 멀티미디어 컨텐츠 중 가장 큰 비중을 차지하는 영상 및 오디오 컨텐츠에 대한 압축 및 전송 기술이 요구된다. 현재 여러 분야에서 영상 및 오디오에 대한 압축 표준으로는 MPEG 이 자리잡았다. 그리고 MPEG에 대한 많은 개선 노력이 있었으며 특히 테스트 모델인 TM5를 비롯한 많은 연구에서 벡터 추출이나 양자화를 이용한 방법을 중심으로 비트율을 제어하기 위한 부호화기 모델이 제시되었다. 본 논문에서는 기존의 연구 접근 방식과는 다르게 프레임 유형간의 거리를 이용하여 영상의 특성에 따라 보다 적합한 프레임 구조를 찾아 제안하였다. 즉 영상의 복잡도와 변화도에 따라 영상의 종류를 구분하고 각 종류별 영상에 대한 표준 MPEG 인코딩 화질을 기준으로 삼은 후, GOP구조 내에서 프레임 유형간의 거리를 조정하여 화질을 손상하지 않고 가장 적은 비트율을 보상하는 프레임구조를 실험 및 분석을 통해 찾아 제안하였다.