• 한국인터넷방송통신학회논문지
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• 제19권1호
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• pp.69-75
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• 2019

과표본화 이산 웨이브렛 변환의 가장 대표적으로 응용되는 분야는 디지털 영상에 존재하는 잡음을 제거하는 기술이다. 이중 밀도 이산 웨이브렛 변환을 이중 트리 이산 웨이브렛 변환과 비교하면, 거의 유사한 특징을 가진다. 본 논문에서는 잡음이 포함된 디지털 영상에 여러 이산 웨이브렛 변환들을 수행하고 생성된 부대역에 임계값 처리 기법을 적용하여 잡음을 제거한 다음 복원한 영상의 성능을 평가하는 실험을 수행하였다. 적당한 임계값을 설정하여 효과적인 잡음제거가 가능하다. 본 논문에서는 여러 방법의 실험 결과에서 제안하는 3방향 분리처리 2차원 이중 밀도 이산 웨이브렛 변환 방법이 우수하다는 것을 확인할 수 있었다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제1권1호
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• pp.24-28
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• 2001

Wavelet transforms are used for implementing digital watermarking methods in the frequency domain. In this paper, we construct the digital watermarking using various wavelet transforms such as the Daubechies transform, Coiflets transform, Symlets transform and the biorthogonal transform, and we compare each digital watermarking method with the others. We investigate the preservation of the watermark after the data compression attack based on the discrete on the discrete cosine transform. We show that the biorthogonal wavelet, denoted by bior3.5, has the best performance among the wavelet types we selected in an experiment.

• International Journal of Control, Automation, and Systems
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• 제4권3호
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• pp.365-371
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• 2006

This paper presents an algorithm based on a combination of Discrete Wavelet Transforms and neural networks for detection and classification of internal faults in a two-winding three-phase transformer. Fault conditions of the transformer are simulated using ATP/EMTP in order to obtain current signals. The training process for the neural network and fault diagnosis decision are implemented using toolboxes on MATLAB/Simulink. Various cases and fault types based on Thailand electricity transmission and distribution systems are studied to verify the validity of the algorithm. It is found that the proposed method gives a satisfactory accuracy, and will be particularly useful in a development of a modern differential relay for a transformer protection scheme.

• 한국원자력학회:학술대회논문집
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• 한국원자력학회 1997년도 추계학술발표회논문집(1)
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• pp.225-230
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• 1997

Discrete Wavelet Transforms (DWTs) are recent mathematics, and begin to be used in various fields. The wavelet transform can be used to compress the signal and image due to its inherent properties. We applied the wavelet transform compression and reconstruction to the neutron cross section data. Numerical tests illustrate that tile signal compression using wavelet is very effective to reduce the data saving spaces.

• International Journal of Computer Science & Network Security
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• 제23권4호
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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.

• 대한전기학회논문지:시스템및제어부문D
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• 제50권10호
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• pp.473-478
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• 2001

Image processings using the two-dimensional wavelet transform (2DWT) have been a very active research area in recent years because the 2DWT possess many good properties. However, the discrete 2DWT can not be used for pattern recognition directly because it does not have the translation property. In this paper, we show why conventional discrete two-dimensional wavelet transforms cannot be used for pattern recognitions directly. Then, we propose a new method that makes it possible to use discrete 2DWT to pattern recognition without modification of standard pyramidal algorithms. The main idea of our method is to postprocess the wavelet transformed images using the second-order neural network. To justify the validity of the method, evaluations with test images were performed. The effectiveness of the method can be shown by the evaluation results.

• International Journal of Ocean Engineering and Technology Speciallssue:Selected Papers
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• 제6권1호
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• pp.1-6
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• 2003

This study presents the results of series of studies, which are mainly devoted to the application of wavelet transforms to various problems in ocean engineering. Both continuous and discrete wavelet transforms were used. These studies attempted to solve detection of wave directionality, detection of wave profile, and decoupling of the rolling component from free roll decay tests. The results of these analysis, using wavelet transform, demonstrated that the wavelet transform can be a useful tool in analyzing many problems in the filed of ocean engineering.

• 한국해양공학회지
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• 제17권3호
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• pp.1-6
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• 2003

This study presents the results of series of studies, which are mainly devoted to the application of wavelet transforms to various problems in ocean engineering. Both continuous and discrete wavelet transforms were used. These studies attempted to solve detection of wave directionality, detection of wave profile, and decoupling of the rolling component from free roll decay tests. The results of these analysis, using wavelet transform, demonstrated that the wavelet transform can be a useful tool in analyzing many problems in the filed of ocean engineering.

• 한국자기공명학회논문지
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• 제4권2호
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• pp.103-115
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• 2000

Wavelet transforms are introduced as a new tool to distinguish real peaks from the noise contaminated NMR data in this paper. New algorithms of two wavelet transforms including Daubechies wavelet transform as a discrete and orthogonal wavelet transform (DWT) and Morlet wavelet transform as a continuous and nonorthogonal wavelet transform(CWT) were developed fer noise elimination. DWT and CWT method were successfully applied to the noise reduction in spectrum. The inevitable distortion of NMR spectral baseline and the imperfection in noise elimination were observed in DWT method while CWT method gives a better baseline ahape and a well noise suppressed spectrum.

• 한국해양공학회:학술대회논문집
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• 한국해양공학회 2003년도 춘계학술대회 논문집
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• pp.324-329
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• 2003

Spectral analysis is an important signal processing tool for time series data. The transformation of a time series into the frequency domain is the basis for a significant number of processing algorithms and interpretive methods. Recently developed transforms based on the new mathematical field of wavelet analysis bypass the resolution limitation and offer superior spectral decomposition. The discrete wavelet transform of Sonar data provides spectral localization of noises, hence noises can be filtered out successfully.