• Proceedings of the Korean Information Science Society Conference
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• 2000.10b
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• pp.212-214
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• 2000

본 논문은 웨이브릿을 기반으로 하는 EZW(Embedded Zerotree Wavelet) 복호기의 설계와 구현에 대하여 소개한다. EZW 부호화는 zerotree를 이용하는 부호화 방법으로서 웨이브릿 변환된 영상이 지니고 있는 계수의 특징을 잘 활용한 부호화 방법이다. EZW 복호화는 EZW 부호화와 대칭 관계를 갖는 구조로 구성되어 있다. EZW 복호기는 부호화의 결과로 생성된 파일의 bit stream을 입력으로 받아서 dominant와 subordinate pass로 구성된 2-pass의 EZW 복호화 과정을 수행하여 부호화 이전의 웨이브릿 변환된 입력 영상의 계수값을 복원한다. 복원된 웨이브릿 변환된 영상의 계수 값은 IDWT(Inverse Discrete Wavelet Transform)를 수행하여 부호화 되기 이전의 원래의 영상으로 재구성된다.

• The Transactions of the Korea Information Processing Society
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• v.5 no.4
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• pp.1048-1056
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• 1998

In this paper, a fractal image coding based on discrete wavelet transform is proposed to improve PSNR at low bit rates and reduce computational complexity of encoding process. The proposed method takes the absolute value of discrete wavelet transform coefficients, and then constructs significant coefficients trees, which indicate the positions and signs of the significant coefficients. This method improves PSNR and reduces computational complexity of mapping contracted domain pool onto range block, by matching only the significant coefficients of range block to coefficients of contracted domain block. Also, this paper proposes a classification scheme which minimizes the number of contracted domain blocks compared with range block. This scheme significantly reduces the number of range and contracted domain block comparison.

• Journal of the Korea Computer Industry Society
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• v.3 no.9
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• pp.1287-1294
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• 2002

The algorithm method for progressive image coding based on discrete wavelet transform presented in a paper. After discrete wavelet transform and extract edge information through edge detection, and then designed efficient coding method more then established embedded coding algorithm using expanded EZW algorithm. Generally, edges have a relatively higher influence on image reconstruction. Occurred DWT on image, and can classify significant coefficients and non-significant coefficients. Using property that edge part has appeared significant coefficient in the paper. Especially, we confirmed that higher frequency sub region on DWT image present homogenous direction property. And on embedded coding, which are effective and well-directed information have higher priority to image reconstruction on transmission. Therefore, our technique algorithm system perform better than that of the conventional method such as progressive image coding application.

• Journal of Broadcast Engineering
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• v.4 no.2
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• pp.127-133
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• 1999

The conventional fractal image compression based on discrete wavelet transform uses the fixed block size in fractal coding and reduces PSNR at low bit rate. This paper proposes a fractal image coding based on discrete wavelet transform which improves PSNR by using variable block size in fractal coding. In the proposed method. the absolute values of discrete wavelet transform coefficients are computed. and the discrete wavelet transform coefficients of different highpass subbands corresponding to the same spatial block are assembled. and the fractal code for the range block of each range block level is assigned. and then a decision tree C. the set of choices among fractal coding. "0" encoding. and scalar quantization is generated and a set of scalar quantizers q is chosen. And then the wavelet coefficients. fractal codes. and the choice items in the decision tree are entropy coded by using an adaptive arithmetic coder. This proposed method improved PSNR at low bit rate and could achieve a blockless reconstructed image. As the results of experiment. the proposed method obtained better PSNR and higher compression ratio than the conventional fractal coding method and wavelet transform coding.rm coding.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2002.05a
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• pp.594-597
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• 2002

In this paper we study the effects of transmission noise on fixed-length coded wavelet coefficients. We use a posteriori detectors which include inter-bitplane information and determine which transmitted codeword was most likely corrupted into a received erroneous codeword We present a simple method of recovering from these errors once detected and demonstrate our restoration methodology on scalar-quantized wavelet coefficients that have been transmitted across a binary symmetric channel.

• Journal of the Korea Society of Computer and Information
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• v.8 no.3
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• pp.47-52
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• 2003

In this paper. a new wavelet packet image coder is proposed for images that include many high-frequency components using the relation between subbands. The new algorithm presents parent-child relationship for reducing image reconstruction error using relations between individual frequency subbands. By parent-child relationship, every coefficient is partitioned and encoded for the zerotree structure. It demonstrates higher PSNR under the same bit rate. These results show that the encoding process of the proposed coder is more accurate than the conventional ones for images that include many high-frequency elements.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9C
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• pp.898-907
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• 2003

In this paper, we propose a new blind watermarking method that embeds a watermark on the lowest wavelet subband coefficients, while most watermarking techniques embed watermarks in the middle frequency range for robustness and fidelity. A new embedding algorithm for watermarking is proposed that embeds a bi-level watermark sequence into randomly selected wavelet coefficients on the lowest subband(LL) using a quantization in order to be robust. Experimental results prove our novel embedding strategy is invisible and good rate-distortion-robustness performance.

• The Journal of the Acoustical Society of Korea
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• v.33 no.2
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• pp.139-145
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• 2014

In this paper, a feature parameter is obtained by applying the Teager energy to the WPD(Wavelet Packet Decomposition) coefficients. The threshold value is obtained based on means and standard deviations of nonspeech frames. Experimental results by using TIMIT speech and NOISEX-92 noise databases show that the proposed algorithm is superior to the typical VAD algorithm. The ROC(Receiver Operating Characteristics) curves are used to compare performance of VAD's for SNR values of ranging from 10 to -10 dB.

• Science of Emotion and Sensibility
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• v.7 no.2
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• pp.141-148
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• 2004

This paper proposed a new time adapted threshold using the standard deviations of Wavelet coefficients after Wavelet transform by frame scale. The time adapted threshold is set up using the sum of standard deviations of Wavelet coefficient in cA3 and weighted cDl. cA3 coefficients represent the voiced sound with low frequency and cDl coefficients represent the unvoiced sound with high frequency. From simulation results, it is demonstrated that the proposed algorithm improves SNR and MSE performance more than Wavelet transform and Wavelet packet transform does. Moreover, the reconstructed signals by the proposed algorithm resemble the original signal in terms of plosive sound, fricative sound and affricate sound but Wavelet transform and Wavelet packet transform reduce those sounds seriously.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.8C
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• pp.795-802
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• 2003

It is very important to construct statistical model in order to exactly estimate the signal variance from a noisy image. In order to estimate variance, information of neighboring region is used generally. The size of neighbor region is varied according to the regional characteristics of image. More accurate estimation of edge variance is due to smaller region of neighbor, on the other hands, larger region of neighbor is used to estimate the variance of flat region. By using estimated variance of original image, in general, Wiener filter is constructed, and it is applied to the noisy image. In this paper, we propose a new method for determining the range of neighbors to estimate the variance in wavelet domain. Firstly, a significance map is constructed using the parent-child relationship of wavelet domain. Based on the number of the significant wavelet coefficients, the range of neighbors is determined and then the variance of the original signal is estimated using ML(maximum likelihood method. Experimental results show that the proposed method yields better results than conventional methods for image denoising.