• Journal of the Institute of Electronics Engineers of Korea SP
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• v.38 no.6
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• pp.703-711
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• 2001

In this paper, we propose efficient multispectral image compression using variable block size vector quantization (VQ). In wavelet domain, we perform the variable block size VQ to remove intraband redundancy for a reference band image that has the lowest spatial variance and the best correlation with other band. And in wavelet domain, we perform the classified interband prediction to remove interband redundancy for the remaining bands. Then error wavelet coefficients between original image and predicted image are residual variable block size vector quantized to reduce prediction error. Experiments on remotely sensed satellite image show that coding efficiency of the proposed method is better than that of the conventional method.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.9
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• pp.927-938
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• 1992

In 1-D subband coding system, a quadrature mirror filter (QMF) pair can be used to split a signal into two subbands and to reconstruct the original signal. In this paper, a pair of 1-D reconstruction filter for the subband coding system is introduced and a coding technique with classified vector quantization, based on energy distributions, for 16 subband images is presented. As computer simulation results show that the method can give similar perceptual quality with bit rate reduced by $20{\sim}30%$ of that of ordinary vector quantization.

• Proceedings of the Korea Contents Association Conference
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• 2004.11a
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• pp.211-214
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• 2004

Former Vector Quantization-based digital watermarking was operated by the user codebook which is combined by the basic and extented codebook. The design way of extended codebook is very important, but still not proposed the concrete way. This paper proposes how to make the basic and extended codebook using the weight of distance. The proposed way can always get the standardizing codebook without inputing watermark.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.21 no.2
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• pp.167-172
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• 2002

The EVRC (Enhanced Variable Rate Codec) is currently in service as a speech cosec in digital cellular systems in North America and Korea. In the EVRC, the LSP (Line Spectral Pairs) related to energy distribution of speech signals in the frequency domain are coded by weighted split vector quantization. Considering that the LSP codebooks might be trained with the language of the develop country of the codebooks or English, it is expected that codebooks trained with Korean provide the performance improvements in the communication in Korean. In this paper, the EVRC LSP codebooks are designed with korean adopting the LBG algorithm based vector quantization, and the performance improvement of the vector quantization and the accompanying speech quality improvement are demonstrated by spectral distortion, SNR and SegSNR measurements, respectively.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.3 s.303
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• pp.81-90
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• 2005

When we transmit signals, which are quantized by the vector quantizer (VQ), through noisy channels, the overall performance of the coding system is very dependent on the employed quantization scheme and the channel error effect. In order to design an optimal coding system, the source and channel coding scheme should be jointly optimized as in the channel-optimized VQ. As a suboptimal approach, we may consider the robust VQ (RVQ). In RVQ, we consider developing an index assignment function for mapping the output of quantizers to channel symbols so that the effect of the channel errors is minimized. Recently, a VQ, which can reduce the encoding complexity and is called the sample-adaptive product quantizer (SAPQ), has been proposed. SAPQ has very similar quantizer structure as to the product quantizer (PQ). However, the quantization performance can be better than PQ. Further, the encoding complexity and the memory requirement for the codebooks are lower than the regular full-search VQ case. In this paper, SAPQ is employed in order to design an RVQ to channel errors by reducing the vector dimension. Discussions on the codebook structure of SAPQ and experiments are introduced in an aspect of robustness to noisy channels.

• The Journal of the Acoustical Society of Korea
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• v.14 no.1E
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• pp.46-55
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• 1995

In this paper, we present a new wavelet transform-based CELP coder, called band selection wavelet transform CELP (BS-WTCELP) operated at 4.8 kbps. The proposed algorithm uses a band selection scheme of frequency bands of wavelet transform and selective vector quantization (VQ). The band selection and selective VQ structure is implemented by using a classified VQ structure. The proposed algorithm has about 0.5-1.0 dB improvement in segmental SNR compared with the conventional CELP that uses the random codebook search, while is has significantly reduced computational and storage complexity. Many experimental results have shown that the proposed algorithm is more suitable for most real-applications than the conventional CELP and wavelet transform CELP.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2391-2400
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• 1999

Vector quantizer (VQ) is an efficient data compression technique for low bit rate applications. However, the major disadvantage of VQ is its encoding complexity which increases dramatically as the vector dimension and bit rate increase. Even though one can use a modified VQ to reduce the encoding complexity, it is nearly impossible to implement such a VQ at a high bit rate or for a large vector dimension because of the enormously large memory requirement for the codebook and the very large training sequence (TS) size. To overcome this difficulty, in this paper we propose a novel structurally constrained VQ for the high bit rate and the large vector dimension cases in order to obtain VQ-level performance. Furthermore, this VQ can be extended to the low bit rate applications. The proposed quantization scheme has a form of feed-forward adaptive quantizer with a short adaptation period. Hence, we call this quantization scheme sample-adaptive product quantizer (SAPQ). SAPQ can provide a 2 ~3dB improvement over the Lloyd-Max scalar quantizers.

• Journal of the Korean Association of Geographic Information Studies
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• v.3 no.1
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• pp.1-11
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• 2000

The hybrid coding algorithm for multi-spectral image obtained from satellite is discussed. As the spatial and spectral resolution of satellite image are rapidly increasing, there are enormous amounts of data to be processed for computer processing and data transmission. Therefore an efficient coding algorithm is essential for multi-spectral image processing. In this paper, VQ(vector quantization), quadtree decomposition, and DCT(discrete cosine transform) are combined to compress the multi-spectral image. VQ is employed for predictive coding by using the fact that each band of multi-spectral image has the same spatial feature, and DCT is for the compression of residual image. Moreover, the image is decomposed into quadtree structure in order to allocate the data bit according to the information content within the image block to improve the coding efficiency. Computer simulation on Landsat TM image shows the validity of the proposed coding algorithm.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.7
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• pp.964-969
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• 2007

In this paper, we propose the image watermarking method for good compression ratio and satisfactory image quality of the cover image and the embedding image. This method is based on the singular value decomposition and the vector quantization using fuzzy c-mean clustering. Experimental results show that the embedding image has invisibility and robustness to various serious attacks. The advantage of this watermarking method is that we can achieve both the compression and the watermarking method for the copyright protection simultaneously.