• Proceedings of the IEEK Conference
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• 1998.10a
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• pp.1251-1254
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• 1998

본 논문에서는 최근들어 널리 연구되고 있는 다해상도 신호해석 방법인 웨이브렛 변환, 웨이브렛 패킷, 그리고 코사인 패킷 알고리듬을 음성개선에 이용하여 각각의 성능을 비교하였으며, 또한 이를 기존의 스펙트럼차감법의 성능과 비교 분석 하였다. 성능비교의 척도로는 SNR과 ㅋ스트랄 거리를 이용하였다. 실험결과 SNR면에서는 코사인 패킷이 가장 좋은 결과를 보였다. 그리고 ㅋ스트랄 거리의 경우 코사인 패킷과 웨이브렛 패켓이 훨씬 나은 결과를 보였으며 주관적인 청취결과 역시 코사인 패킷이 가장 좋은 결과를 보였고, 기존의 스펙트럼 차감법은 musical noise의 영향으로 인해 상대적으로 다른 방식에 비해 합성음의 음질이 많이 떨어짐을 확인할 수 있었다.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04a
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• pp.877-879
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• 2002

본 논문에서는 HVS을 이용한 웨이브렛 패킷 기반 이미지 워터마킹 기법을 제안한다. 이미지를 주파수/공간 도메인 상에서 세부적으로 분해하기 위해 웨이브렛 패킷 분해방법을 선택했고 워터마크 삽입 후 사람 눈에 안보일 수 있도록 MTF를 참고하여 워터마크를 삽입하였다. 모든 서브 밴드에 랜덤 가우시안 백터에 의해 생성된 1000개의 워터마크를 골고루 삽입함으로써 견고성측면을 강화하였다. 실험 결과는 이런 비가시성과 가우시안 노이즈나 JPEG, 잘라내기등 여러 공격모델에 대해 견고성을 잘 보여주고 있다.

• 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.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.36S no.7
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• pp.134-135
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• 1999

This paper presents a speech enhancement method with spectral subtraction using wavelet, wavelet packet and cosine packet transforms which are known as multiresolutional signal analysis method. The performance of each method is compared with the conventional spectral subtraction method. Performance assessments based on average SNR, cepstral distance and informal subjective listening test are carried out. Experimental result demonstrate that cosine packet shows the best result in objective performance measure as well as subjective shows less musical noise than the conventional spectral subtraction method after removing the noise components.

• Proceedings of the KSPS conference
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• 2003.10a
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• pp.105-108
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• 2003

본 논문은 잡음 환경에서의 음성인식을 위하여 음성에 부가된 잡음을 제거하는 방법으로 프레임 단위로 웨이브렛 변환 영역의 표준편차를 활용하여 시간 적응적 임계값을 사용하는 새로운 방법을 제안한다. 웨이브렛 변환영역의 cD1과 cA3의 표준편차 값을 이용하여 임계값을 설정함으로써 음성의 변화에 적응할 수 있도록 하였다. 또한 묵음구간의 잔여 잡음을 제거하기 위한 방법을 제안하였다. 실험을 통하여 제안한 방법이 기존의 웨이브렛 변환과 웨이브렛 패킷 변환을 이용한 잡음제거 방법보다 SNR(Signal to Noise Ratio)과 MSE(Mean Squared Error) 측면에서 향상됨을 확인할 수 있었다.

• The Journal of Information Technology
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• v.2 no.2
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• pp.127-138
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• 1999

The wavelet transform is widely used in signal processing application. In this paper, a wavelet domain adaptive algorithm(WPTNLMS) is derived and its performances are evaluated in non-stationary environment. Where the input signals are decomposed by the wavelet packet transform for the multi-resolution adaptive processing. And the NLMS is used as an adaptive algorithm in wavelet domain. The proposed technique is applied to noise cancellation of the Doppler signal which is added with white Gaussian noise.

• Journal of Broadcast Engineering
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• v.7 no.1
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• pp.55-65
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• 2002

Wavelet transform has recently emerged as a promising technique for video processing applications due to its flexibility in representing non-stationary video signals. Motion estimation which uses wavelet transform of octave band division method is applied In many places but if motion estimation error happens in the lowest frequency band. motion estimation error is accumulated by next time strep and there has the Problem that time and the data amount that are cost In calculation at each steps are increased. On the other hand. wavelet packet that achieved the best image quality in a given bit rate from a rate-distortion sense is suggested. But, this method has the disadvantage of time costs on designing wavelet packet. In order to solve this problem we solved this problem by introducing Top_down method. But we did not find the optimum solution in a given butt rate. That image variance can represent image complexity is considered in this paper. In this paper. we propose a fast multiresolution motion estimation scheme based on the adaptive wavelet transform for video compression.

• Journal of KIISE:Software and Applications
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• v.29 no.8
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• pp.521-528
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• 2002

We propose a new approach to the feature selection for the classification of handwritten characters using two-dimensional(2D) wavelet packet bases. To extract key features of an image data, for the dimension reduction Principal Component Analysis(PCA) has been most frequently used. However PCA relies on the eigenvalue system, it is not only sensitive to outliers and perturbations, but has a tendency to select only global features. Since the important features for the image data are often characterized by local information such as edges and spikes, PCA does not provide good solutions to such problems. Also solving an eigenvalue system usually requires high cost in its computation. In this paper, the original data is transformed with 2D wavelet packet bases and the best discriminant basis is searched, from which relevant features are selected. In contrast to PCA solutions, the fast selection of detailed features as well as global features is possible by virtue of the good properties of wavelets. Experiment results on the recognition rates of PCA and our approach are compared to show the performance of the proposed method.

• The Journal of the Acoustical Society of Korea
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• v.22 no.8
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• pp.670-679
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• 2003

This paper deals with application of wavelet transform, which is known to be good for time-frequency analysis, in order to detect the underwater transient signals embedded in ambient noise. A new detector of acoustic transient signals is presented. It combines two detection tools: wavelet analysis and higher-order statistics. Using both techniques, the detection of the transient signal is possible in low signal to noise ratio condition. The proposed algorithm uses the wavelet transform of a partition of the signal on frequency domain, and then higher-order statistics tests the Gaussian nature of the segments.

• The Journal of the Acoustical Society of Korea
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• v.22 no.2
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• pp.153-161
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• 2003

In this paper, we propose a wavelet-based detection method to identify efficiently the time-delay or multipath channel of ocean acoustic signals due to complex ocean medium and boundary layers. Our proposed method employs wavelet packet transform to analyze the received broadband acoustic signals and applies the matched filter to determine the time region of interest. Also, we present numerical testing that results on both the simulated and real data revealed the efficiency of this method in time-delay estimation and moreover its capability in estimating the time-delay of individual path in multipath channel, in which the arrival patterns are too close to be separated by the matched filter method.