• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.1
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• pp.8-15
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• 2005

The analysis of Rader signal that have non-linearity variable phase is signal that contact easily in several fields such as radar, telecommunication, seismic, sonar and biomedical applications. In generally, Non-stationary signal means that spectral characteristics are varying with time and instantaneous frequency is only one frequency or narrow range of frequencies varying as a function of time. Therefore, Instantaneous frequency is vary important variable that understanding physical characteristic of signal. This paper was describes continuous wavelet transform to determine instantaneous frequency at non-staionary signal and compare to existing method. When white noise or various frequency is overlapped each other in sign, existing method was can not decide corrected instantaneous frequency, but when used continuous wavelet transform, very well decide correctly frequency regardless of component of signal.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• v.10 no.1
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• pp.47-60
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• 2006

Due to the uneven illumination of FPD panel surface, it is difficult to detect the defects. The paper proposes a method to find the uneven illumination compensation using wavelets, which are done based on multi-resolution structure. The first step is to decompose the image into multi-resolution levels. Second, elimination of lowest smooth sub-image with highest frequency band removes the high frequency noise and low varying illumination. In particular, the main algorithm was implemented by lifting scheme for realtime inline process.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.6
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• pp.743-748
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• 2009

In this paper, we propose an effective method to extract background components in automated vision inspection system for polarized film used in TFT LCD display panels. The test image signals are typically composed of three components such as ununiform background, random noises and target defect signals. It is important to analyze the background signal for accurate extraction of defect components. Two dimensional continuous wavelets with first derivative gaussian is used. This methods can be applied for reliable extraction of defect signal by elimination of the background signal from the original image. The proposed method outperforms over conventional FFT methods.

• International Journal of Precision Engineering and Manufacturing
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• v.6 no.4
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• pp.26-30
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• 2005

A rotor run-up or run-down process provide more useful information for modal analysis than normal operation conditions. A traditional difficulty associated with rotor run-up or run-down analysis is the non-stationary nature of vibration data. This paper compares Short-Time Fourier Transform (STFT) and the wavelets analysis in these non-stationary signal analyses. An Adaptive Wavelet Analysis (AWT) is proposed to analyze these signals. Although simulations and experiments in a simple rotor-bearing system show that both STFT and AWT can be used to analyze non-stationary vibration signals in rotor dynamics, proposed AWT provides better results than STFT analysis. From the amplitude-frequency curve obtained by AWT, the modal frequency and damping ratio are calculated. This paper also analyzes the characteristics of signals when the shaft touches the outer hoop in a run-up process. The AWT can give a good result in this complex dynamic analysis of the touching process.

• Journal of Korea Multimedia Society
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• v.17 no.3
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• pp.287-293
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• 2014

Early fire detection is very important to avoid loss of lives and material damage. The conventional smoke detector sensors have difficulties in detecting smoke in large outdoor areas. The video-based smoke detection can overcome these drawbacks. This paper proposes a new smoke detection method in video sequences. It uses the ratio of variation rate of subband energy in the wavelet transform domain. In order to reduce the false alarm, candidate smoke blocks are detected by using motion, decrease of chromaticity and the average intensity of block in the YUV color space. Finally, it decides whether the candidate smoke blocks are smokes or not by using their temporal changes of subband energies in the wavelet transform domain. Experimental results show that the proposed method noticeably increases the accuracy of smoke detection and reduces false alarm compared with the conventional smoke detection methods using wavelets.

• Journal of Navigation and Port Research
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• v.32 no.10
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• pp.777-783
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• 2008

Nowadays wavelet transforms are widely used for the analyses of PIV velocity vector fields. This is bemuse the wavelet provides not only spatial information of the velocity vectors but also of time and frequency domains. In this study, a discrete wavelet trC1f1$form has been applied to real PIV images of bubbly flows. The vector fields obtained by a self-made cross-correlation PIV algorithm were used for the discrete wavelet transform The performances of the discrete wavelet transform is investigated by changing the level of power of discretization. The decomposed images by the wavelet multiresolution showed conspicuous characteristics of the bubbly flows according to the level changes. The high spatial bubble concentrated area could be evaluated by the constructed discrete wavelet transform algorithm, at which high leveled wavelets could play a dominant roles to reveal the flow characteristics.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 1996.06a
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• pp.159-163
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• 1996

In this paper, a new image compression technique, which uses lifting scheme and pyramid vector quantization, is proposed. Lifting scheme is a new technique to generate wavelets and to perform wavelet transform, and pyramid vector quantization is a kind of vector quantization which dose not have codebook neither codebook generation algorithm. For the purpose of realizing more compression rate, an arithmetic entropy coder is used. Proposed algorithm is compared with other wavelet based image coder and with JPEG which uses DCT and adaptive Huffman entropy coder. Simulation results showed that the performance of proposed algorithm is much better than that of others in point of PSNR and bpp.

• Proceedings of the Korean Nuclear Society Conference
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• 1998.05b
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• pp.705-710
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• 1998

We describe a multigrid wavelet-based natural pixel (WNP) method for image reconstruction in emission computed tomography (ECT). The ECT is used to identify the tagged radioactive material's position in the body for detection of abnormal tissue such as tumor or cancer, as in SPECT and PET. With ECT methodology in parallel beam mode, we formulate a matrix-based reconstruction method for radionuclide sources in the human body. The resulting matrix for a practical problem is very large and nearly singular. To overcome this ill-conditioning, wavelet transform is considered in this study. Wavelets have inherent de-noising and multiscale resolution properties. Therefore, the multigrid wavelet-based natural pixel (WNP) method is very efficient to reconstruct image from projection data that is noisy and incomplete. We test this multigrid wavelet natural pixel (WNP) reconstruction method with the MCNP generated projection data for diagnosis of the simulated cancerous tumor.

• Proceedings of the Korea Multimedia Society Conference
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• 1998.04a
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• pp.110-115
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• 1998

웨이브릿 해석에서 CWT(continuous wavelet transform)에서는 Plancherel 형태의 복원 정리가 성립하고, 웨이브릿 급수는 frame 이론과 다해상도 이론(multiresolution analysis)을 활용한 이산복원정리가 성립한다. 복원정리가 만들어짐에 따라 이에 상응하는 웨이브릿이 생성되는데, CWT에서는 허용조건(admissibility condition)을 만족하는 basic wavelet이고, 웨이브릿 급수에서는 MRA를 이용한 Daubechies 웨이브릿, frame 이론을 이용한 Meyer 웨이브릿 등을 생각할 수 있다. 본 연구에서는 CWT에서 사용한 허용조건을 자연스럽게 확장함으로써 기존의 것보다 간편하고 활용도가 우수한 이산복원정리를 발견하고, 이에 상응하는 보다 만들기 쉬운 새로운 형태의 L1 웨이브릿군을 개발함을 목적으로 한다. 본 연구에 개발한 새로운 웨이브릿을 사용하여 시간-주파수에서의 신호 복원 및 분석에 응용한다.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.224-227
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• 2004

From 1980's, the DWT(Discrete Wavelet Transform) is applied to the data/image processing. Many people use the DWT in remote sensing for diversity purposes and they are satisfied with the wavelet theory. Though the algorithm for wavelet is very diverse, many people use the standard wavelet such as Daubechies D4 wavelet and biorthogonal 9/7 wavelet. We will overview the wavelet theory for discrete form which can be applied to the image processing. First, we will introduce the basic DWT algorithm and review the wavelet algorithm: EZW (Embedded Zerotree Wavelet), SPIHT(Set Partitioning in Hierarchical Trees), Lifting scheme, Curvelet, etc. Finally, we will suggest the properties of wavelet algorithm; and wavelet filter for each image processing in remote sensing.