• The Journal of the Korea Contents Association
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• v.2 no.4
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• pp.23-29
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• 2002

This paper suggest the image compression that is needed to process PACS in medical information system. The image decoding method is used Linear-predictor and Lloyd-Max quantizer(quantization) in the Wavelet transform domain. Wavelet Transform Method is processed the multi-resolution by dividing image into 10 sub-bands of 3 levels. Low frequency domain that is sensitive to human visual characteristic is encoded by DPCM which is lossless encoding methods, and Lloyed-Max quantizer, the optimal quantizer for reducing ringing and aliasing in the image of inter sub-band, is used in the remaining high frequency domain of sub-band. The examination verifies that decompressed images are superior by the result that PSNR is 28.53dB on the input image, 512$\times$152 abdominal CT image and Chest image.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.7
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• pp.26-32
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• 1994

The Lloyd-Max algorithm is an iterative scheme for design of the minimum mean square error quantizer. It is very simple in concept and easy to program into a computer. However its convergence and accuracy are primarily dependent upon the accuracy of the initial parameter. In this paper, a new initial parameter which converges to a specific value when the number of output levels becomes large is selected. And an estimator using curve fitting techique is suggested. In addition, performance of the proposed method is shown to be superior to that of the existing methods in accuracy and convergence.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.3
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• pp.69-79
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• 1994

DCT image coding has been well known for its compression efficiency. Its nature makes it also suitable for efficient progressive transmission and reconstruction since low frequency transform coefficients contain most of the energy of image signals. In this paper, we propose a progressive transmission technique of DCT image by non-sequential bit ordering using Lloyd-Max quantizer. And then, we will show that the Lloyd-Max quantizer can be embedded quantization. In simulation results, the proposed method show better subjective picture and MSE of the reconstructed image than the conventional zig-zag scanning transmission of transform coefficients.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.85-88
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• 2000

Signal splitting and perfect reconstruction in subband coding is based on the assumption that quantization errors are negligible. But if subband signal is quantized, 4 types of errors occurs thus it is not impossible to do perfect reconstruction. These errors are QMF design error, aliasing error, signal error and random error. By using the QMF for subband splitting, the QMF error does not present. and by using the Lloyd-Max quantizer for the quantization and by using an appropriate synthesis filter, all signal dependent errors can be cancelled and the remaining error is random error which is uncorrelated with the original image〔1〕. In this thesis, Lenna and Camera-Man image are devided into 10 subbands by using the D4 and D20 wavelet And the subband signals are quantized by using the Lloyd-Max quantizer and the quantization errors are compared. and evaluated.

• 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 information and communication convergence engineering
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• v.9 no.2
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• pp.193-196
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• 2011

Transmit antenna selection techniques are prominent since they exploit the spatial selectivity at the transmitter side. In the literature, antenna selection techniques assume full knowledge of the channel state information (CSI). In this paper, we consider that the CSI is not perfectly known at the transmitter; however, a quantized version of the channel coefficients is fed back by the users. We employ the non-uniform Lloyd-Max quantization algorithm which takes into consideration the distribution of the channel coefficients. Simulation results show that the degradation in the BER of the system with imperfect CSI at the transmitter is tolerable, especially when the transmit diversity order is high.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.49 no.1
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• pp.19-30
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• 2012

For digital data compression, the quantization is the main part of the lossy source coding. In order to improve the performance of quantization, the vector quantizer(VQ) can be employed. The encoding complexity, however, exponentially increases as the vector dimension or bit rate gets large. Much research has been conducted to alleviate such problems of VQ. Especially for high bit rates, a constrained VQ, which is called the sample-adaptive product quantizer(SAPQ), has been proposed for reducing the hugh encoding complexity of regular VQs. SAPQ has very similar structure as to the product VQ(PQ). However, the quantizer performance can be better than the PQ case. Further, the encoding complexity and the memory requirement for the codebooks are lower than the regular full-search VQ case. Among SAPQs, 1-SAPQ has a simple quantizer structure, where each product codebook is symmetric with respect to the diagonal line in the underlying vector space. It is known that 1-SAPQ shows a good performance for i.i.d. sources. In this paper, a study on designing 1-SAPQ for the first-order Markov process. For an efficient design of 1-SAPQ, an algorithm for the initial codebook is proposed, and through the numerical analysis it is shown that 1-SAPQ shows better quantizer distortion than the VQ case, of which encoding complexity is similar to that of 1-SAPQ, and shows distortions, which are close to that of the DPCM(differential pulse coded modulation) scheme with the Lloyd-Max quantizer.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.12B
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• pp.2382-2390
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• 1999

In this paper, we employed a new quantization scheme called sample-adaptive product quantizer (SAPQ) to quantize image data based on the differential pulse code modulation (DPCM) coder, which has fixed length outputs and high bit rates. In order to improve the performance of traditional DPCM coders, the scalar quantizer should be replaced by the vector quantizer (VQ). As the bit rate increases, it will be nearly impossible to implement a conventional VQ or modified VQ, such as the tree-structured VQ, even if the modified VQ can significantly reduce the encoding complexity. SAPQ has a form of the feed-forward adaptive scalar quantizer having a short adaptation period. However, since SAPQ is a structurally constrained VQ, SAPQ can achieve VQ-level performance with a low encoding complexity. Since SAPQ has a scalar quantizer structure, by using the traditional scalar value predictors, we can easily apply SAPQ to DPCM coders. For synthetic data and real images, by employing SAPQ as the quantizer part of DPCM coders, we obtained a 2~3 dB improvement over the DPCM coders, which are based on the Lloyd-Max scalar quantizers, for data rates above 4 b/point.

• Journal of Broadcast Engineering
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• v.2 no.1
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• pp.74-83
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• 1997

We have proposed a composite feature measure which combines the color and shape features of an image for image retrieval. We improved the performance of retrieval based on the efficient color quantization using the Lloyd-Max quanizer and on the Histogram matrix matching method which considers the spatial correlation of quantized color group. We also supplemented the color information using shape information with the Improved Moment Invarlants. We have tested our technique on Image database consisting of 200 actual trademark images. Our experimental results showed that our approach improved the performance compared to the previous method under the various situations such as rotation images, translation images, noise added images, gamma corrected images and so on. The efficiency of retrieval is found to be very high and experimental results are