• Proceedings of the Korea Society of Information Technology Applications Conference
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• 2007.05a
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• pp.9-28
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• 2007

It is well known that wavelet transform is a signal processing technique which can display the signals on in both time and frequency domain. In this paper, we proposed a new approach based on stationary wavelet transform to provide an enhanced approach for eliminating noise. A 'stationary wavelet transform', where the coefficient sequences are not decimated at each stage, is described. The testing result on sample iris images has shown an enhanced image quality and also show that it has a superior performance than traditional discrete wavelet transform.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.57 no.2
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• pp.184-190
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• 2008

The fault location algorithm based on stationary wavelet transform was developed to locate the fault point more accurately. The stationary wavelet transform(SWT) was introduced instead of conventional discrete wavelet transform(DWT) because SWT has redundancy properties which is more useful in noise signal processing. In previous paper, noise cancellation technique based on the correlation of wavelet coefficients at multi-scales was introduced, and the efficiency was also proved in full. In this paper, fault section discrimination and fault location algorithm using noise cancellation technique were tested by ATP simulation on real power cable systems. From these results, the fault can be located even in very difficult and complicated situations such as different inception angle and fault resistance.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.28 no.3
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• pp.84-90
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• 2014

The partial discharge of Cast-resin Transformer has a difficulty to be analyzed, because it is an abnormal condition signal of which stochastic characteristics varies with time variance. In this study, background noise coming from the outside of the cast-resin transformers through ground wire can be removed and only a discharge signal of which defects are simulated can be obtained, using the wavelet transform method, which is a time-frequency domain analysis technique. As a result, it was confirmed that de-noising using the SWT technique is the best efficient among three methods of the wavelet transform techniques.

• 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

• 한국지구과학회:학술대회논문집
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• 2005.09a
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• pp.400-407
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• 2005

웨이브렛 변환(Wavelet Transform)은 시간영역과 주파수영역에서 동시에 분석이 가능하고 불연속적인 자료를 분석하는데 유리하기 때문에 그동안 영상을 처리하고 분석하는데 널리 이용되어 왔다. Discrete Wavelet Transform(DWT)는 주어진 영상에서 특성 정보는 유지하면서 다른 여러 종류의 계수로 분해 할 수 있게 해주기 때문에, 계수에 임계치를 적용해 고주파 성분을 제거하면 잡음을 줄일 수 있다. Stationary Wavelet Transform(SWT)는 DWT에서 다운샘플링에 의해 발생하는 문제점을 해결하기 위한 변환방법으로 잡음제거에 DWT보다 효과적이라고 알려져 있다. 이 연구에서는 DWT와 SWT에 의한 필터링을 광학영상과 레이더 영상에 적용하여 보고, 기존의 필터링 기법과 그 결과를 비교하였다. 그 결과 SWT에 의한 방법이 경계성분은 보존하면서 잡음을 가장 효과적으로 줄일 수 있었다.

• Proceedings of the KIEE Conference
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• 2006.07a
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• pp.440-441
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• 2006

The fault location algorithm based on wavelet transform was developed to locate the fault more accuracy after the operation of relay. The stationary wavelet transform(SWT) was introduced instead of conventional discrete wavelet transform(DWT) because SWT has redundancy properties which is more useful in noise signal processing. The algorithm was based on the correlation of wavelet coefficients at multi-scales. Fault location algorithm was tested by simulation on real power cable system. From these results, the fault can be located even in very difficult situations, such as at different inception angle and fault resistance.

• Proceedings of the KIEE Conference
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• summer
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• pp.557-559
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• 2004

The study of applying wavelet transform in power cable system fault location has been recognized by many researchers and investigated. For performance of fault location, the fault generated transients can be captured at one end of the cable or both ends. Between two approaches, single-ended approach is less expensive and more reliable as it doesn't need communication link between the ends of the cable. So, we performs the approach based on the one. In this paper, we are going to introduce a new algorithm to discriminate the transient and the reflected signal using wavelet coefficient. For wavelet transform, the stationary wavelet transform(SWT) is applied instead of conventional DWT because SWT has redundancy properties which is more useful in noisy signal processing.

• Journal of Advanced Navigation Technology
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• v.22 no.5
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• pp.359-366
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• 2018

In this paper, the noise is removed by using CTLS aircraft installed FBG sensor inside the aircraft wing. We suggest a normal wavelet transform scheme with motion - invariant characteristics for noise reduction. In the case of installing FBG sensors inside the composite material as in CTLS, large and small empty spaces and parts or sections are generated between the adhesive layers, and a signal splitting problem occurs. FBG sensor is not affected by noise. but eletromagnetic, light source, light detector and signal processing device are influeced by noise because these are eletronic components what affected by eletromagnetic wave. because of this, errors are occured. Experimental results show that the noise can be removed using normal wavelet transform and more accurate data detection is possible.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.476-484
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• 2018

The high capacity audio watermarking algorithms are facing a main challenge in satisfying the robustness against attacks especially on de-synchronization attacks. In this paper, a robust and a high capacity algorithm is proposed using segment selection, Stationary Wavelet Transform (SWT) and the Quantization Index Modulation (QIM) techniques along with new synchronization mechanism. The proposed algorithm provides enhanced trade-off between robustness, imperceptibility, and capacity. The achieved watermarking improves the reliability of the available watermarking methods and shows high robustness towards signal processing (manipulating) attacks especially the de-synchronization attacks such as cropping, jittering, and zero inserting attacks. For imperceptibility evaluation, high signal to noise ratio values of above 22 dB has been achieved. Also subjective test with volunteer listeners shows that the proposed method has high imperceptibility with Subjective Difference Grade (SDG) of 4.76. Meanwhile, high rational capacity up to 176.4 bps is also achieved.

• International Journal of Computer Science & Network Security
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• v.23 no.4
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• pp.39-47
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• 2023

This study compares various transformation techniques for multifocus image fusion. Multi-focus image fusion is a procedure of merging multiple images captured at unalike focus distances to produce a single composite image with improved sharpness and clarity. In this research, the purpose is to compare different popular frequency domain approaches for multi-focus image fusion, such as Discrete Wavelet Transforms (DWT), Stationary Wavelet Transforms (SWT), DCT-based Laplacian Pyramid (DCT-LP), Discrete Cosine Harmonic Wavelet Transform (DC-HWT), and Dual-Tree Complex Wavelet Transform (DT-CWT). The objective is to increase the understanding of these transformation techniques and how they can be utilized in conjunction with one another. The analysis will evaluate the 10 most crucial parameters and highlight the unique features of each method. The results will help determine which transformation technique is the best for multi-focus image fusion applications. Based on the visual and statistical analysis, it is suggested that the DCT-LP is the most appropriate technique, but the results also provide valuable insights into choosing the right approach.