• ETRI Journal
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• v.28 no.1
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• pp.51-58
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• 2006

In this paper, we propose a method of applying a lifting-based wavelet domain e-median filter (LBWDEMF) for image restoration. LBWDEMF helps in reducing the number of computations. An e-median filter is a type of modified median filter that processes each pixel of the output of a standard median filter in a binary manner, keeping the output of the median filter unchanged or replacing it with the original pixel value. Binary decision-making is controlled by comparing the absolute difference of the median filter output and the original image to a preset threshold. In addition, the advantage of LBWDEMF is that probabilities of encountering root images are spread over sub-band images, and therefore the e-median filter is unlikely to encounter root images at an early stage of iterations and generates a better result as iteration increases. The proposed method transforms an image into the wavelet domain using lifting-based wavelet filters, then applies an e-median filter in the wavelet domain, transforms the result into the spatial domain, and finally goes through one spatial domain e-median filter to produce the final restored image. Moreover, in order to validate the effectiveness of the proposed method we compare the result obtained using the proposed method to those using a spatial domain median filter (SDMF), spatial domain e-median filter (SDEMF), and wavelet thresholding method. Experimental results show that the proposed method is superior to SDMF, SDEMF, and wavelet thresholding in terms of image restoration.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.32A no.9
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• pp.1244-1249
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• 1995

Wavelet transform technique is applied to two important electromagnetic problems:1) to analyze the frequency-domain radar echo from finite-size targets and 2) to the integral solution of two- dimensional electromagnetic scattering problems. Since the frequency- domain radar echo consists of both small-scale natural resonances and large-scale scattering center information, the multiresolution property of the wavelet transform is well suited for analyzing such ulti-scale signals. Wavelet analysis examples of backscattered data from an open- ended waveguide cavity are presented. The different scattering mechanisms are clearly resolved in the wavelet-domain representation. In the wavelet transform domain, the moment method impedance matrix becomes sparse and sparse matrix algorithms can be utilized to solve the resulting matrix equationl. Using the fast wavelet transform in conjunction with the conjugate gradient method, we present the time performance for the solution of a dihedral corner reflector. The total computational time is found to be reduced.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2000.06a
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• pp.269-273
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• 2000

This paper describes Active Noise Control (ANC) using Discrete Wavelet Transform (DWT) Domain Least Mean Square (LMS) Method. DWT-LMS is one of the transform domain input decorrelation LMS and improves the convergence speed of adaptive filter especially when the input signal is highly correlated. Conventional transform domain LMS's use Discrete Cosine Transform (DCT) because it offers linear band signal decomposition and fast transform algorithm. Wavelet transform can project the input signal into the several octave band subspace and offers more efficient sliding fast transform algorithm. In this paper, we propose Wavelet transform domain LMS algorithm and shows its performance is similar to DCT LMS in some cases using ANC simulation.

• Structural Engineering and Mechanics
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• v.78 no.3
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• pp.369-378
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• 2021

This paper reviewed a few output-only system identification algorithms and identified the shortcomings of those popular blind source separation methods. To address the issues such as less sensors than the targeted modal modes (under-determinate problem), repeated natural frequencies as well as systems with complex mode shapes, this paper proposed a complex wavelet modified second order blind identification method (CWMSOBI) by transforming the time domain problem into time-frequency domain. The wavelet coefficients with different dominant frequencies can be used to address the under-determinate problem, while complex mode shapes are addressed by introducing the complex wavelet transformation. Numerical simulations with both high and low signal-to-noise ratios validate that CWMSOBI can overcome the above-mentioned issues while obtaining more accurate identified results than other blind identification methods.

• Journal of Biomedical Engineering Research
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• v.17 no.3
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• pp.347-354
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• 1996

This paper presents digital hearing aids signal processing system in WT(wavelet transform) domain. For implementation of hearing aids in WT domain, the gain in frequency domain is approximated in WT domain. We also present the gain selection algorithm to deal with the change of input signal power. Most transform methods produce blocking effect, and this effect degrades the convergence rate of feedback canceller. As a solution, we proposed wavelet transform bascd feedback canceller. To evaluate the performance, we compared it with LOT (lapped orthogonal transform) method in the frequency domain. This system has not shown the blocking effect, and improves convergence rate as compared with the LOT based feedback canceller.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.6
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• pp.517-526
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• 2015

Among the various image fusion or pan-sharpening methods, those wavelet-based methods provide superior radiometric quality. However, the fusion processing is not only simple but also flexible, since many low- and high-frequency sub-bands are often produced in the wavelet domain. To address this issue, a novel DT-CWT (Dual-Tree Complex Wavelet Transform) proportional to the fusion method by a WZP (Wavelet Zero-Padding) is proposed. The proposed method produces a single high-frequency image in the spatial domain that is injected into the LRM (Low-Resolution Multispectral) image. Thus, a wavelet domain fusion can be simplified to spatial domain fusion. In addition, in the proposed DT-CWTP (DT-CWT Proportional) fusion method, it is unnecessary to decompose the LRM image by adopting WZP. The comparison indicates that the proposed fusion method is nearly five times faster than the DT-CWT with SW (Substitute-Wavelet) fusion method, meanwhile simultaneously maintaining the radiometric quality. The conducted experiments with WorldView-2 satellite images demonstrated promising results with the computation efficiency and fused image quality.

• Journal of the Korean Society for Precision Engineering
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• v.13 no.9
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• pp.31-37
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• 1996

This Paper is concerned with effective signal identification method for tool breakage and micro chipping using discrete wavelet transform of feed motor current in milling operations. The wavelet transform uses an analyzing waveletfunction which is localized in both frequency and time domain to detect subtle time localized changes in input signals. The changing pattern of wavelet coefficient is continuously compared to detect tool breakage and micro chipping over one spindle revolution. The results indicate that the wavelet transform can identify tool failure with much greater sensi- tivity than the time domain monitoring and frequency domain monitoring such as FFT. Experimental results are presented to support the proposed scheme.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.32B no.9
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• pp.1188-1197
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• 1995

This paper describes an algorithm that reduces computational requirement of the Kalman filter and estimates the signal efficiently. The reference signals are mapped onto the orthogonal wavelet transform domain so that the eigenvalue spread of its autocorrelation matrix could be smaller than that in the time domain. In the wavelet transform domain the autocorrelation matrix is nearly diagonal. Therefore, the transformed signal can be decomposed each orthogonal elements. The Kalman filter can be applied to each orthogonal elements and computational requirement is reduced. The possibility of applying the parallel Kalman filter was verified through the theory and simulation. The eigenvalue spread in the wavelet transform domain is smaller 8.35 times than that in the time domain and the computational requirement is reduced from 1.4 times to 2. 93 times than that of the conventional Kalman filter.

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2002.05a
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• pp.213-217
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• 2002

Recently the subject of "wavelet analysis" has be drawn by both mathematical and engineering application fields such as Signal Processing, Compression/Decomposition, Wavelet-Neural Network, Statistics and etc. Even though its similar to courier analysis, wavelet is a versatile tool with much mathematical content and great potential for applications. Especially, wavelet transform uses localizable various mother wavelet functions in time-frequency domain. Therefore, wavelet transform has good time-analysis ability for high frequency component, and has good frequency-analysis ability for low frequency component. Using the discriminative ability is more easy method than other conventional techniques. In this paper, Morlet wavelet transform was applied to discriminate the kind of line fault by acquired data from real power transformation network. The experimental result presented that Morlet wavelet transform is easier, and more useful method than the FFW (Fast courier Transform).ransform).

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.12 no.7
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• pp.1110-1114
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• 2001

The discrete wavelet concept in the k-domain is applied to efficiently represent Green function of integral equations. Application of discrete wavelet concept to Green function in the k-domain can be implemented equivalently by using spatial domain variable-sized windows. The proposed method consists of constant Q-filtering, changing the center of coordinates, and transforming spatially filtered Green functions into those in the k-domain. A mathematical expression of Green function based on the discrete wavelet concept is derived and its characteristics are discussed.