• Journal of the Institute of Convergence Signal Processing
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• v.15 no.4
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• pp.141-147
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• 2014

The wavelet shrinkage is a technique that reduces the wavelet coefficients to minimize the MSE(Mean Square Error) between the signal and the noisy signal by making use of the threshold determined by the variance of the wavelet coefficients. In this paper, by using the monotonic transform and the power of wavelet subbands, new thresholds applicable to the high and the low frequency wavelet bands are proposed, and the thresholds are applied to the ST(soft-threshold) technique to denoise on image signals with additive Gaussian noise. And the results of PSNRs are compared with the results obtained by the VisuShrink technique and those of [15]. The results shows the validity of this technique.

• Proceedings of the IEEK Conference
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• 2000.11c
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• pp.85-88
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• 2000

With the rapid growth of network distributions of digitized media(audio, image, and video), there is an urgent need for copyright protection. For now watermarking is a well-known technique for copyright protection of digital data. To embed a digital watermark to the image, discrete cosine transform(DCT) and wavelet transform are commonly used. In this paper, the performance of the DCT based watermarking technique and wavelet based watermarking technique were compared and the influences of the parameter a that decides the strength of the watermarking data were considered.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.488-490
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• 2001

It is important to catch or classify fault types by any detecting technique for distribution protection. This paper proposes the technique to classify the fault types using wavelet transform in radial distribution line. Modeling of the radial distribution line is simulated using PSCAD/EMTDC and wavelet transform is performed in the Matlab program.

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.521-524
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• 1999

In spite of advances in image resolution and film contrast, check screen/film mammography remains one of diagnostic imaging modality where the image interpretation is very difficult. For the enhancement of film mammography, in this paper, dyadic wavelet transform is introduced. An unsharp masking technique is proposed and performed in wavelet domain. In addition, simple nonlinear enhancement and a denosing stage that preserves edges using wavelet shrinkage are computed into this technique. In this paper. we propose a new method for the gain setting of nonlinear enhancement and show result and comparison.

• KIEE International Transactions on Power Engineering
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• v.11A no.4
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• pp.1-8
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• 2001

This paper presents a discrete wavelet transform approach for detecting voltage sags initialized by fault conditions and starting of larger motors. The proposed technique is based on utilizing the summation value of D1(at scale 1) coefficients in multiresolution analysis(MRA) based on the discrete wavelet transform. In this paper, the proposed technique is tested under various cases of voltage sags. It is shown that the voltage sag detection technique based on the wavelet transform is a satisfactory and reliable method for detecting voltage sags in power quality disturbance analysis.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.4D
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• pp.581-586
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• 2006

Incidents, which is unexpected unusual events such as traffic accidents, have increased on the most roads in Korea. The obstruction of a fluent traffic flow occurred by incidents causes the traffic congestion and decreases the capacity. The Wavelet technique was applied to detect the road section and the happening time of incidents on urban freeways in this study, and this technique has been widely used in many engineering fields such as an electrical engineering, etc. The availability and validity of the Wavelet technique to the detection of incidents was examined by the occupancy rate, the important element of traffic flows, which is extracted from the data of detectors installed on Seoul Urban freeways. Then, this result is compared to the California Algorithm and the Low-Pass Filtering Algorithm among basic present detection algorithms, which are based on the occupancy rate. As a result, the false alarm rate of this method was similar as that of the California algorithm and the Low-Pass Filtering algorithm, but the detection rate is higher.

• KIEE International Transactions on Power Engineering
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• v.3A no.3
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• pp.130-138
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• 2003

This paper presents a discrete wavelet transform approach for determining the beginning and end times of voltage sags. Firstly, investigations in the use of some typical mother wavelets, namely Daubechies, Symlets, Coiflets and Biorthogonal are carried out and the most appropriate mother wavelet is selected. The proposed technique is based on utilizing the maximum value of Dl (at scale 1) coefficients in multiresolution analysis (MRA) based on the discrete wavelet transform. The results are compared with other methods for determining voltage sag duration, such as the Root Mean Square (RMS) voltage and Short Time Fourier Transform (STFT) methods. It is shown that the voltage sag detection technique based on the wavelet transform is a satisfactory and reliable method for detecting voltage sags in power quality disturbance analysis.

• 제어로봇시스템학회:학술대회논문집
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• 2005.06a
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• pp.2006-2009
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• 2005

This paper presents a method for registering images using phase correlation technique in fourier domain, hough transform and multi-resolution wavelet. To register images, source and input images are transformed to wavelet domain. An angular transition can be obtained by applying hough transform technique followed by phase correlation. Then we apply phase correlation technique to find x-axis and y-axis transition. We apply wavelet transform to reduce processing time and also use its coefficients as edge information instead of canny detector. With multi-resolution property of wavelet transform, registration time can be greatly reduced. After we get all transition parameters, we transform the input images according to these parameters. Then, we compose and blend all images into a new large image with details of all source images. From our experiment, we can find the accurate transition both x-y translation and angular transition with less error.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2004.10a
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• pp.429-436
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• 2004

For the in-situ health monitoring of critical members in civil infra-structures, ultrasonic guided Lamb waves-based non-destructive evaluation (NDE) is very suitable. However, a chief drawback of the Lamb wave techniques is that multiple modes exist at all frequencies and the modes are generally dispersive, which means that the received signals may be very complicated. To overcome these complications, selective transmitting and receiving of a single A/sub 0/ mode within a frequency range can be adopted. Furthermore, a wavelet technique can be utilized to decompose the Lamb wave response into wavelet coefficients as a tool for signal processing. The changes in the Lamb waves interacting with damages in the steel plates are successfully characterized by this wavelet technique, through the amplitude change of the wavelet coefficients. In this paper, the feasibility of detecting a line crack on the surface of a steel plate and loosened bolts in a joint steel specimen using the Lamb waves and the wavelet technique is investigated.

• Proceedings of the KIEE Conference
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• 1999.11b
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• pp.210-212
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• 1999

This paper proposes a novel wavelet transform based technique for prediction of System Marginal Price(SMP). In this paper, Daubechies D1(haar), D2, D4 wavelet transforms are adopted to predict SMP and the numerical results reveal that certain wavelet components can effectively be used to identify the SMP characteristics with relation to the system demand in electric power systems. The wavelet coefficients associated with certain frequency and time localisation are adjusted using the conventional multiple regression method and then reconstructed in order to predict the SMP on the next scheduling day through a five-scale synthesis technique. The outcome of the study clearly indicates that the proposed wavelet transform approach can be used as an attractive and effective means for the SMP forecasting.