• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.505-508
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• 2005

Wavelet scheme can be applied to the various remote sensing problems: conventional multi-resolution image analysis, compression of large image sets, fusion of heterogeneous sensor image and segmentation of features. In this study, we attempted wavelet-based filtering and its analysis. Traditionally, statistical methods and adaptive filter are used to manipulate noises in the image processing procedure. While we tried to filter random noise from optical image and radar image using Discrete Wavelet Transform (DW1) and Stationary Wavelet Transform (SW1) and compared with existing methods such as median filter and adaptive filter. In result, SWT preserved boundaries and reduced noises most effectively. If appropriate thresholds are used, wavelet filtering will be applied to detect road boundaries, buildings, cars and other complex features from high-resolution imagery in an urban environment as well as noise filtering

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.18 no.4
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• pp.381-387
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• 2009

The end-milling force behaviour is very complex and it is related to a de-noising phenomenon, so it is very difficult to detect and diagnose this static cutting force phenomenon. This paper presents a new method of filtering of end-milling force in end-milling operation using filter bank technique, based on the wavelet transform. In this paper by comparing the history of end-milling force using wavelet filtering the fundamental end-milling property of the wavelet transform is well reviewed and analyzed. This result of wavelet transform using filter bank shows the possible static prediction of end-milling force with severe dynamic properties such as chatter in end-milling operation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.236-237
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• 2019

In this paper, we propose a wavelet - based image noise reduction algorithm. We develop wavelet transform of existing Mallat Tree method. First, we propose a multiple filtering method. Maximizes the energy concentration characteristic of the wavelet transform considering the energy of each subband in the wavelet domain. We apply the proposed multiple filtering to the noise image. Finds energy subbands that can not be seen in normal images and removes them to remove noise.

• The Journal of Engineering Geology
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• v.27 no.4
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• pp.513-518
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• 2017

Groundroll is a coherent noise showing dispersive behavior in land seismic-reflection records and its rejection has been a stubborn problem in data processing because they severely degrade the continuities and resolution of reflection signals. Conventional processing schemes of attenuating noises are the kind of frequency filtering (i.e., bandpass and f-k) that uses the Fourier transform (FT) along the entire trace in the time domain. To suppress them in this study, 1D wavelet filtering (WT) that can control time-varying frequency properties is tested and performed in the land-based synthetic and field seismic data. The results are compared to the ones from conventional filtering techniques in terms of continuities and resolution of reflection events. This filtering technique enhanced the reflection events by effectively eliminating the dispersive groundroll and random noises with control of time-scale function on wavelet domain.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.16 no.2
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• pp.113-122
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• 2016

In this paper, we suggest a approach which comprises fast Fourier transform inversion by wavelet noise attenuation. It represents an inverse filtering by adopting a factor into the Wiener filtering, and the optimal factor is chosen to minimize the overall mean squared error. in order to apply the Wiener filter, we have to compute the power spectrum of original image from the corrupted figure. Since the Wiener filtering contains the inverse filtering process, it expands the noise when the blurring filter is not invertible. To remove the large noises, the best is to remove the noise using wavelet threshold. Wavelet noise attenuation steps are consisted of inverse filtering and noise reduction by Wavelet functions. experimental results have not outperformed the other methods over the overall restoration performance.

• Proceedings of the KIEE Conference
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• 2003.07c
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• pp.1845-1848
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• 2003

PD(Partial Discharge) signal have the range from several kHz to several GHz. External noises don't give any interference to discerning PD signals with high frequency bandwidth between several hundreds MHz to several GHz but, in the range between several decades kHz to several MHz, are big obstacles to prevent from discriminating PD signals. Therefore, selecting appropriate filter to decrease the influence of noise is important problem. PD signals have the characteristics both short duration and non-continuous pulse train. For separating PD signals from External noises, some different filtering methods different from conventional ones are needed and wavelet filtering method was convinced to be suitable filtering method in various investigations. This paper has simulated PD signal and various noises and investigated the influences for the performance of wavelet filter by varying the components relative to designing of wavelet filter and constructed suitable one. For the purpose of convincing the performance of wavelet filter, real PDs were produced in needle to plane electrode structure. This small PD signal was mixed with external noises and filtered with wavelet filter. We have obtained apparent PD signals and noises are well suppressed by wavelet filter.

• Journal of the Korean Society of Radiology
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• v.2 no.1
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• pp.23-29
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• 2008

The present study proposed a method that dissolves ultrasonographic images into multiple resolutions using wavelet conversion and a boundary detection filter and improves the quality of ultrasonographic images through boundary detection filtering. In order to reduce noises and strengthen edges, the proposed method adjusted selectivity coefficient by area step by step from a low resolution image obtained from wavelet converted images to a high resolution image and performed edge filtering in consideration of direction. Through this method, we generated a selective low pass filtering effect in areas except edges by decreasing the wavelet coefficient for pixels in spot areas, improved continuity by smoothing edges in the tangential direction, and enhanced contrast by thinning in the normal direction. Through an experiment, we compared the filtering method using a non linear anisotropic expansion model and the filtering method using wavelet contraction structure in single resolution.

• Structural Engineering and Mechanics
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• v.56 no.3
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• pp.423-442
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• 2015

This study examines the wavelet transform for output-only system identification of ambient excited engineering structures with emphasis on its utilization for modal parameter estimation of high-order and closely-spaced modes. Sophisticated time-frequency resolution analysis has been carried out by employing the modified complex Morlet wavelet function for better adaption and flexibility of the time-frequency resolution to extract two closely-spaced frequencies. Furthermore, bandwidth refinement techniques such as a bandwidth resolution adaptation, a broadband filtering technique and a narrowband filtering one have been proposed in the study for the special treatments of high-order and closely-spaced modal parameter estimation. Ambient responses of a 5-story steel frame building have been used in the numerical example, using the proposed bandwidth refinement techniques, for estimating the modal parameters of the high-order and closely-spaced modes. The first five natural frequencies and damping ratios of the structure have been estimated; furthermore, the comparison among the various proposed bandwidth refinement techniques has also been examined.

• Tribology and Lubricants
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• v.24 no.6
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• pp.320-325
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• 2008

The recent industrial application requires technical methods to get the cutting fluid droplet surfaces in particular from the viewpoint of topography and micro texture. To characterize the surface topography of droplet, the combination of the confocal laser scanning microscope (CLSM) and wavelet filtering is well suited for obtaining the droplet geometry encountered in tribological research. This technique indicates a better agreement in obtaining an appropriate droplet surface obtained by the CLSM over a detail range of surface accuracy (resolution: $2{\mu}m$). And the results allow an excellent accuracy in a measurement of a droplet surface. The combination of extended focal depth measurement configured and multi-scale wavelet filtering has proven that it can construct a droplet surface in a successive and accurate way. A multi-scale approach of wavelet filtering was developed based on the decomposition and reconstruction of droplet surface by 2D wavelet transform using db9 (a mother wavelet of daubechies). Also this technique can be extended to characterize the quantification of droplet properties and other field in a wide range of scales. Finally this method is verified to be a better droplet surface modeling in a micro scale arising in a mist machining.

• International journal of advanced smart convergence
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• v.1 no.1
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• pp.48-51
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• 2012

The conventional method for filtering force plate data, low-pass filtering, does not always give accurate results when applied to force data from a custom-made, instrumented treadmill. Therefore, this study compares low-pass filtered data to the same data passed through a wavelet filter. We collected data with the treadmill running. However these include motor noise with ground reaction force at two force plates. We found that he proposed wavelet method eliminated motor noise to result in more accurate force plate data than the conventional low-pass filter, particularly at high speed motor operation. In this study we suggested the convolution wavelet (CNW) which was compared to that of a low-pass filter. The CNW showed better performance as compared to band-pass filtering particularly for low signal-to-noise ratios, and a lower computational load.