• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.6
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• pp.111-117
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• 2007

This paper presents a novel approach to speech enhancement based on a complex Laplacian probability density function (pdf). With a use of goodness-of-fit (GOF) test we show that the complex Laplacian pdf is more suitable to describe the conventional Gaussian pdf. The likelihood ratio (LR) is applied to derive the speech absence probability in the speech enhancement algorithm. The performance of the proposed algorithm is evaluated by the objective test and yields better results compared with the conventional Gaussian pdf-based scheme.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6C
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• pp.857-864
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• 2004

Many image compression standards such as JPEG, MPEG or H.263 are based on the discrete cosine transform (DCT) and quantization method. Quantization error. is the major source of image quality degradation. The current dequantization method assumes the uniform distribution of the DCT coefficients. Therefore the dequantization value is the center of each quantization interval. However DCT coefficients are regarded to follow Laplacian probability density function (pdf). The center value of each interval is not optimal in reducing squared error. We use mean of the quantization interval assuming Laplacian pdf, and show the effect of correction on image quality. Also, we compare existing quantization error to corrected quantization error in closed form. The effect of PSNR improvements due to the compensation to the real image is in the range of 0.2 ∼0.4 ㏈. The maximum correction value is 1.66 ㏈.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.13 no.1
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• pp.12-18
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• 1988

It is found that the estimation pdf of the real intraframe DPCM prediction error by $x^3$ goodness-of-fit test for the images is nearer gamma distribution that laplacian. Also the new pdf estimation method by NMAE is proposed and applied to the pdf adaptive DPCM system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11A
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• pp.1957-1962
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• 2001

Image and video compression requires quantization error model of DCT coefficients for post processing, restoration or transcoding. Once DCT coefficients are quantized, it is impossible to recover the original distribution. We assume that the original probability density function (pdf) is the Laplacian function. We calculate the variance of the quantized variable, and estimate the variance of the DCT coefficients. We can confirm that the proposed method enhances the accuracy of the quantization error estimation.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06a
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• pp.9-15
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• 1996

In this paper, we propose a new detector based on the median-shift sign. We call it the median-shift sign (MSS) detector, which is an extension of the classical sign detector. We first analyze the problem of detecting a dc signal in noise of known probability density function (pdf). The MSS detector with the optimum median-shift value, the optimum MSS detector, performs better than the sign detector in Gaussian noise: it has the best performance among the detectors compared in Laplacian and Cauchy noise. It is shown that the MSS detectors with constant median-shift values are nearly equal to the optimum MSS detector. We also analyze the problem of detecting a dc signal when only partial information is available on the noise. The MSS detectors with constant median-shift values are almost equal to the sign detector in Gaussian noise: they perform better than the sign and Wilcoxon detectors for most signal ranges in Laplacian and Cauchy noise.

• Journal of the Korean Institute of Telematics and Electronics
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• v.25 no.6
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• pp.591-597
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• 1988

In this paper, we have studied a channel capacity affected by noise which produces burst errors in the ISDN(approx 140Kbps) data transmission using a existing PSTN. First, a digital communication system model to apply a subscriber line to a narrow band ISDN channel is presented. Second, the decision methodology of a channel capacity limitation whether the pdf of the noise generated by a waveform synthesizer is Pisson or Laplacian is described. As a result of the simulation, we have obtained that the Poission distributed noise is approached to the Guassian rather than the Laplacian under the same SNR condition.

• Journal of Broadcast Engineering
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• v.11 no.4 s.33
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• pp.386-395
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• 2006

Multi-view video coding technology demands the very high efficient coding technologies, because it has to encode a number of video sequences which are achieved from a number of video cameras. For this purpose, multi-view video coding introduces the inter-view prediction scheme between different views, but it shows a limitation of coding performance enhancement by adopting only new prediction method. Accordingly, we are going to achieve the more coding performance by enhancing dequantizer perfermance. Multi-view video coding is implemented basically based on H.264/AVC and uses the same quantization/de-quantization method as H.264/AVC does. The conventional quantizer and dequantizer is designed with the assumption that input residual signal follows the Laplacian PDF. However, it doesn't follow the fixed PDF type always. This mismatch between assumption and real data causes degradation of coding performance. To solve this problem, we propose the efficient de-quantization method based on quantized coefficients distribution at decoder without extra information. The extensive simulation results show that the proposed algorithm produces maximum $1.5\;dB{\sim}0.6\;dB$ at high bitrate compared with that of conventional method.