• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.263-264
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• 2008

A method for high impedance fault(HIF) detection based on wavelet transform is presented in this paper. HIF is detected and classified by obtaining the energy distribution curve from the wavelet coefficients at each level. The energy distribution of each transient disturbance has unique deviation from sinusoidal wave in particular energy level, which is adopted to provide reliable classification of the type of transient.

• Proceedings of the Korean Information Science Society Conference
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• 1998.10c
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• pp.568-570
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• 1998

본 연구는 Wavelet Transform을 이미지 처리에 적용하여 지적재산권 보호를 위한 Watermarking 기술을 연구하였다. Watermark가 이미지에 Invisible하게 삽입되면서 압축, Filtering, truncation등과 같은 이미지 처리에도 강력한 Watermark 기술 연구에 중점을 두었다. 특히 완벽한 복원을 위하여 Wavelet Transform을 사용하였고, 또한 DCT기술을 접목시킴으로 해서 압축에 강력한 결과를 나타내게 되었다.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.161-164
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• 2002

We propose a new method for rotational image retrieval that it is based on highly related property between a spatial image and wavelet transform. The characteristics have an important role in the design of our algorithm. Our proposed algorithm for rotational image retrieval is to obtain same image or rotated image. Because our algorithm used an rotational image retrieval.

• Proceedings of the IEEK Conference
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• 2002.06d
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• pp.179-182
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• 2002

In this paper, we propose a wavelet based adaptive algorithm which improves the convergence speed and reduces computational complexity using the fast running FIR filtering efficiently We compared the performance of the proposed algorithm with time and frequence domain adaptive algorithm using computer simulation of adaptive noise canceler based on synthesis speech. As the result, the proposed algorithm is suitable for adaptive signal processing area using speech or acoustic field.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2454-2457
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• 1998

In this paper, we interconnected the wavelet transformation and ADPCM to improve the image compression ratio and reduce the loss of information in the reconstructed image. Simulation shows the promising results.

• Proceedings of the KIEE Conference
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• 1998.07g
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• pp.2262-2264
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• 1998

This paper propose a new method for the discrete signal : Discrete Wavelet Transform(DWT). This paper is a brief introduction to the DWT and applies the DWT coding for the audio data as an example. We can have a number of hint about the compression algorithm of multimedia resources and the high performance of transmission and storage.

• Proceedings of the Acoustical Society of Korea Conference
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• autumn
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• pp.319-322
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• 2000

솔레노이드 코일을 이용하여 전자기식 충격파 발생기를 제작하고 발생된 충격파의 음향학적인 특성을 측정하였다. 충격파의 생물학적 효과에 가장 중요한 과정으로 알려진 초점 부위의 기포군의 파열 현상을 바늘형 하이드로폰을 이용하여 평가하였다. 하이드로폰 신호의 웨이브렛 변환을 이용하여 초점 부근에서 기포 파열 지연 시간을 정확히 측정할 수 있음을 보였다.

• Journal of the Semiconductor & Display Technology
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• v.19 no.4
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• pp.77-83
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• 2020

The Linear system analysis for physical system is very powerful tool for system diagnostic utilizing relationship between the input signal and output signal. This method utilized generally to investigate physical properties of system and the nondestructive test by ultrasonic signals. This method can be explained by linear system theory. In this paper the Continuous Wavelets Transform is utilized to search the relation between the linear system and continuous wavelets transform.

• Korean Journal of Remote Sensing
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• v.28 no.4
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• pp.357-367
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• 2012

This paper presents a two-stage methodology for anomaly detection from hyperspectral imagery that consists of transform-based feature extraction and selection, and computation of a local spatial auto-correlation statistic. First, principal component transform and 3D wavelet transform are applied to reduce redundant spectral information from hyperspectral imagery. Then feature selection based on global skewness and the portion of highly skewed sub-areas is followed to find optimal features for anomaly detection. Finally, a local indicator of spatial association (LISA) statistic is computed to account for both spectral and spatial information unlike traditional anomaly detection methodology based only on spectral information. An experiment using airborne CASI imagery is carried out to illustrate the applicability of the proposed anomaly detection methodology. From the experiments, anomaly detection based on the LISA statistic linked with the selection of optimal features outperformed both the traditional RX detector which uses only spectral information, and the case using major principal components with large eigen-values. The combination of low- and high-frequency components by 3D wavelet transform showed the best detection capability, compared with the case using optimal features selected from principal components.

• Journal of the Institute of Convergence Signal Processing
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• v.6 no.2
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• pp.53-58
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• 2005

Points of sharp variations in images are the most important components when we analyze singularities of images. And they include a variety of information about the image's location and shape etc. So a lot of researches for detecting those edges have been continuing even now and at the early stage of the research, edge detection operators used relation among neighborhood pixels. However, such methods do not have excellent performance in the image which exists noise and can not detect edge selectively. In the meantime, the wavelet transform which is presented as a new technique of signal processing field is able to detect multiscale edge and is being applied widely in many fields that analyze singularities such as edge. For this reason, in this paper we detected image's line-edge elements with 2-D wavelet function, which is independent of line's width, in mixed noise environment.