• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.2
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• pp.95-102
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• 1996

This paper describes the realization of a rela-time adaptive acoustic echo canceller, which adopts a microprogramming method, for removing acoustical echoes in speakerphone systems using th eADSP-2101 microprocessor with a pipeline and modified harvard architecture. We apply the LMS (least mean square) algorithm to estimate the coefficients of a transversal FIR filter. For the acustic adaptive echo canceller, we propose a parallel operation programming to imrove algorithm execution speed and apply a nonlinear quantization to reduce the quantization error caused by large dynamic range of voice signal.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.4
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• pp.25-32
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• 1997

In this paper, we propose an adaptive BTC algorithm using the characteristics of the error signals. The BTC algorithm has a avantage that it is low computational complexity, but a disadvantage that it produces the ragged edges in the reconstructed images for th esloping regions beause of coding the input with 2-level signals. Firstly, proposed methods classify the input into low, medium, and high activity blocks based on the variance of th einput. Using 1-level quantizer for low activity block, 2-level for medium, and 4-level for high, it is adaptive methods that reduce bit rates and the inherent quantization noises in the 2-level quantizer. Also, in case of processing high activity block, we propose a new quantization level allocation algorithm using the characteristics of the error signals between the original signals and the reconstructed signals used by 2-level quantizer, in oder that reduce bit rates superior to the conventional 4-level quantizer. Especially, considering the characteristics of input block, we reduce the bit rates without incurrng the visual noises.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.12
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• pp.4624-4642
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• 2014

Image compression is a popular research issue that focuses on the problems of reducing the size of multimedia files. Vector Quantization (VQ) is a well-known lossy compression method which can significantly reduce the size of a digital image while maintaining acceptable visual quality. A locally adaptive scheme (LAS) was proposed to improve the compression rate of VQ in 1997. However, a LAS needs extra indicators to indicate the sources, consequently the compression rate of LAS will be affected. In this paper, we propose a novel method to eliminate the LAS indicators and so improve the compression rate. The proposed method uses the concept of data hiding to conceal the indicators, thus further improving the compression rate of LAS. From experimental results, it is clearly demonstrated that the proposed method can actually eliminate the extra indicators while successfully improving the compression rate of the LAS.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.832-835
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• 2004

In this paper, we proposed a blind watermarking algorithm to use characteristics of a scalar quantizer which is similar with the recommended in the JPEG2000 and JPEG. This algorithm shifts a quantization index according to the value of each watermark bit to prevent losing the watermark information during the compression by quantization. Therefore, the watermark is embedded during the process of quantization, not an additional process for watermarking, and adaptively applied as an assigned quantizer according to application area. In the embedding process, a LFSR(Linear feedback shift register) is used to hide the watermarking positions. Therefore the embedded watermark can be extracted by only the owner who knows the initial value of LFSR without the original image. The experimental results showed that the proposed algorithm satisfies the robustness and imperceptibility corresponding to the major requirement of watermarking.

• The Journal of the Acoustical Society of Korea
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• v.17 no.4E
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• pp.35-40
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• 1998

In this paper, an efficient quantization method of line spectrum pairs(LSP) with cascaded structure of vector quantizer and scalar quantizer is proposed. First, input LSP parameters is vector-quantized using a codebook a with a moderate number of entries. In the second stage of quantization, the components of residual vector are individually quantized by the scalar quantizer. The utilization of ordering property of LSP parameters and the inclusion of interframe prediction improve the quantizer performance and remove the stability check routine after quantization procedure. The new vector-scalar hybrid quantizer using 26 bits/frame shows a transparent quality of speech that an average spectral distortion is 1 dB and the frame proportion with above 2 dB spectral distortion is less than 2%. The performances of proposed quantization method is evaluated in the transmission errors.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.67-75
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• 2012

Optimal quantizers in conducting the entropy-constrained quantization for high bit rates have the lattice structure. The quantization process is simple due to the regular structure, and various quantization algorithms are proposed depending on the lattice. Such a lattice vector quantizer (VQ) can be implemented by using the sample-adaptive product quantizer (SAPQ) and its output can also be easily entropy encoded. In this paper, the entropy encoding scheme for the lattice VQ is proposed based on SAPQ, and the performance of the proposed lattice VQ, which is based on SAPQ with the entropy coder, is asymptotically compared as the rate increases. It is shown by experiment that the gain for the memoryless Gaussian source also approaches the theoretic gain for the uniform density case.

• Journal of Korea Multimedia Society
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• v.9 no.3
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• pp.296-306
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• 2006

We proposed the algorithm for the quantization noise reduction based on variable filter adaptive to edge signal in MPEG postprocessing system. In our algorithm, edge map and local modulus maxima in the decoded images are obtained by using 2D Mallat wavelet tilter. And then, blocking artifacts in inter-block are reduced by Gaussian LPF that is variable to filtering region according to edge map. Ringing artifacts in intra-block are reduced by 2D SAF according to local modulus maxima. Experimental results show that the proposed algorithm was superior to the conventional algorithms as regards PSNR, which was improved by 0.04-0.20 dB, and the subjective image quality.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.5
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• pp.822-832
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• 1994

DSC-HDTV image compression algorithm removes spatial, temporal, and amplitude redundancies of an image by using transform coding, motion-compensated predictive coding, and adaptive quantization, respectively. In this paper, leak processing method which is used to recover image quality quickly from scene change and transmission error and adaptive quantization using perceptual weighting factor obtained by HVS are proposed. Perceptual weighting factor is calculated by contrast sensitivity, spatio-temporal masking and frequency sensitivity. Adaptive quantization uses the perceptual weighting factor and global distortion level from buffer history state. Redundant bits according to adaptation of HVS are used for the next image coding. In the case of scene change, DFD using motion compensated predictive coding has high value, large bit rate and unstabilized buffer states since reconstructed image has large quantization noise. Thus, leak factor is set to 0 for scene change frame and leak factor to 15/16 for next frame, and global distortion level is calculated by using standard deviation. Experimental results show that image quality of the proposed method is recovered after several frames and then buffer status is stabilized.

• 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.

• ETRI Journal
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• v.34 no.5
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• pp.655-665
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• 2012

Based on wideband precoding (WBP) in the multiple-input multiple-output orthogonal frequency division multiplexing system, an adaptive nonuniform codebook is presented in this paper. The relationship between the precoder distribution and spatial correlation is analyzed at first. A closed-form expression based on overlapped isosceles triangles is proposed as an approximation of the precoder distribution. Then, the adaptive codebook design is derived with the approximate distribution to minimize quantization errors. The capacity and bit error rate performance demonstrate that the adaptive codebook with WBP outperforms the conventional fixed uniform codebook.