• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1347-1351
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• 1987

This thesis aims at studying laplacian pyramid vector quantization which keeps a simple compression algorithm and stability against various kinds of image data. To this end, images are devied into two groups according to their statistical characteristics. At 0.860 bits/pixel and 0.360 bits/pixel respectively, laplacian pyramid vector quantization is compared to the existing spatial domain vector quantization and transform coding under the same condition in both objective and subjective value. The laplacian pyramid vector quantization is much more stable against the statistical characteristics of images than the existing vector quantization and transform coding.

• Proceedings of the Korean Society of Computer Information Conference
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• 2018.07a
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• pp.207-208
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• 2018

본 논문에서는 기계학습의 하나인 Learning Vector Quantization 알고리즘을 이용하여 컨트롤러 순서를 정하는 모델을 제안하였다. 제안한 모델은 모든 컨트롤러 정보를 수집하여 Learning Vector Quantization의 LVQ1와 LVQ2 기법을 이용하여 컨트롤러의 순서를 정한다. 이를 통해, 효율적인 컨트롤러 동기화가 이뤄질 것으로 기대된다.

• 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.

• The KIPS Transactions:PartB
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• v.12B no.5 s.101
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• pp.513-520
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• 2005

In this paper, we propose a robust multi-watermarking method based on vector quantization using an index transform function. In contrast with the conventional watermark embedding methods to embed only one watermark at a time into the original image, we present a method to embed multiple watermarks for copyright protection. The proposed method efficiently enhances the robustness by index transform function which minimizes changes of vector quantization indices against various attacks. Experimental results show that the proposed method has a good robustness against various attacks compared with the conventional multi-watermarking method based on vector quantization.

• The Journal of the Acoustical Society of Korea
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• v.17 no.3E
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• pp.53-57
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• 1998

Spectral information at a speech coder should be quantized with sufficient accuracy to keep perceptually transparent output speech. Spectral information at a low bit rate speech coder is usually transformed into corresponding line spectrum pair parameters and is often quantized with a vector quantization algorithm. As the vector quantization algorithm generally has high complexity in the optimal code vector searching routine, the complexity reduction in that routine is investigated using the ordering property of the line spectrum pair. When the proposed complexity reduction algorithm is applied to the well-known split vector quantization algorithm, the 46% complexity reduction is achieved in the distortion measure compu-tation.

• ETRI Journal
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• v.30 no.5
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• pp.738-740
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• 2008

In this paper, block constrained trellis coded vector quantization (BC-TCVQ) is presented for quantizing the line spectrum frequency parameters of the wideband speech codec. Both a predictive structure and a safety-net concept are combined into BC-TCVQ to develop the predictive BC-TCVQ. The performance of this quantization is compared with that of the linear predictive coding vector quantizer used in the AMRWB codec, demonstrating reductions in spectral distortion.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.12
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• pp.72-80
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• 1994

In this paper, we present a digital image data compression method using vector quantization preserving edges. A new vector quantization algorithm is proposed using a new sampling method and edge region extraction. The codebook generation time is faster than existing algorithms and the quality of decompressed images is much improved. Extrimental results suggest that the resultant compression ratio and PSNR are better than those of BPVQ and HMVQ methods.

• Proceedings of the Korean Information Science Society Conference
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• 2001.10a
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• pp.796-798
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• 2001

본 논문에서는 벡터 양자화(Vector Quantization)를 이용해서 소유자의 저작물에 대해 저작권을 보호할 수 있는 디지털 워터마킹(Watermarking) 기법을 제안한다. 소유자의 워터마크 정보로는 사용자 정보를 비밀키를 이용해서 암호화한 데이터를 사용하며, 워터마킹 처리는 원본 이미지를 웨이블렛 기반의 벡터 양자화(Vector Quantization)에 사용되는 코드북(Coodbook)을 이용한다. 코드북을 사용함으로서 양질의 정보를 유지하면서 워터마킹을 효과적으로 처리할 수 있다.

• Proceedings of the IEEK Conference
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• 2003.11a
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• pp.369-372
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• 2003

In this paper, we propose impr oved binary tree vector quantization based on spatial sensitivity which is one of the human visual properties. We combine the weights based on spatial masking effect according to changes of three primary colors in blocks of images with the process of splitting nodes using eigenvector in binary tree vector quantization. The test results show that the proposed method generates the quantized images with fine color and performs better than the conventional method in terms of clustering the similar regions. Also the proposed method can get the better result in subjective qualify test and PSNR.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.11 no.2
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• pp.84-88
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• 2011

In this paper, a new competition strategy for learning vector quantization is proposed. The simple competitive strategy used for learning vector quantization moves the winning prototype which is the closest to the newly given data pattern. We propose a new learning strategy based on k-nearest neighbor prototypes as the winning prototypes. The selection of several prototypes as the winning prototypes guarantees that the updating process occurs more frequently. The design is illustrated with the aid of numeric examples that provide a detailed insight into the performance of the proposed learning strategy.