• 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.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.745-748
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• 1998

Recently, image and voice processing part is using wavelet transform. We propose thining algorithm using wavelet tranform. Wavelet transform consists of low frequency and high frequency in the spatial and frequency domain. After the wavelet decomposition, more than 90 percents of energy are contained in lowest frequency band. Therefor, for images with large difference of gray value between foreground and background like character images, we can more accurately in the lowest frequency band. Lowest frequency band has wavelet transform significant coefficient(WTS) that is required for the thinning algorithm we proposed Paper [3][5][7][8] can not separate consonants and vowels of korean characters. Becuase korean characters have structural feature. This paper can separate consonants and vowels. Simulation executed low frequency image and data compression can reduce 1/4$^{n}$ with level n. we can redcue time complexity 3/8.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.1 no.1
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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.

• Journal of the Korean Magnetic Resonance Society
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• v.5 no.2
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• pp.66-72
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• 2001

The noise suppression of time domain NMR data by discrete wavelet transform with high order Daubechies wavelet coefficients exhibits severe peak distortion and incomplete noise suppression near real signal. However, the fact that even a shift averaged Harr wavelet transform with a set of Daubechies wavelet coefficients (1/2, -l/2) can be used as a new and excellent tool to distinguish real peaks from the noise contaminated NMR signal is introduced. New algorithms of shift averaged Harr wavelet were developed and quantitatively evaluated in terms of threshold and signal to noise ratio (SNR).

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.8
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• pp.50-59
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• 1996

In this paper, a new hierarchical motion estiamtion scheme using the wavelet transformed multi-resolution image layers is proposed. Compared with the full search motion estimation method, the existing hierarchical methods remarkably reduce the amount of the computation but their efficiencies are depreciated by the local minima problem. In order to solve the local minima problem, the multi-resolution image layers are composed using the wavelet transform and the number of layers participated in the motion estimation for a block is determined by considering of its low band energy and higher band energy on the first wavelet transformed layer. The ratio between higher band energy and low band energy of each block is evaluated and in the case of the blocks which include relatively large higher band energy, the motion estimation is carried out in the high resolution layer. Otherwise, all layers are used. The final motion vectors are obtained in the first wavelet transformed layer. So less bits for motion vectors are transmitted, and the decomposition of received image using inverse wavelet transform decreases the blocking effect.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.281-286
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• 2003

Wavelet Transform can effectively represent the local characteristics of a signal in the space-frequency domain. However, the feature vector extracted using wavelet transform is not translation invariant. This paper describes a new feature extraction method using wavelet transform, which is translation-invariant. Based on this translation-invariant feature extraction, the iris recognition method, based on this feature extraction method, is robust to noises. Experimentally, we show that the proposed method produces super performance in iris recognition.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3050-3052
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• 2000

Recently. the subject of "wavelet analysis" has drawn much attention from both mathematical and engineering application fields such as Signal Processing, Compression/ Decomposition, Statistics and etc. Analogous to Fourier analysis, wavelets is a versatile tool with very rich mathematical content and great potential for applications. Specially, wavelet transform uses localizable various mother wavelet functions in time-frequency domain. In this paper, discrimination analyses of acquired electrical current signals for each and mixed loads were tried by using Morlet wavelet transform. Their representative loads were classified as TV, DRY, REF, and FL.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.3224-3226
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• 1999

This paper introduces a nonlinear wavelet transform based on the lifting scheme, which is applied to signal denoising through the translation invariant wavelet transform. The wavelet representation using orthogonal wavelet bases has received widespread attention. Recently the lifting scheme has been developed for the construction of biorthogonal wavelets in the spatial domain. In this paper, we adaptively reduce the vanishing moments in the discontinuities to suppress the ringing artifacts and this customizes wavelet transforms providing an efficient framework for the translation invariant denoising. Special care has been given to the boundaries, where we design a set of different prediction coefficients to reduce the prediction error.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.427-430
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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 Fourier 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 FFT (Fast Fourier Transform).

• East Asian mathematical journal
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• v.26 no.1
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• pp.105-113
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• 2010

In the spectral analysis, Fourier coeffcients are very important to give informations for the original signal f on a finite domain, because they recover f. Also Fourier analysis has extension to wavelet analysis for the whole space R. Various kinds of reconstruction theorems are main subject to analyze signal function f in the field of wavelet analysis. In this paper, we will present a new reconstruction theorem of functions in $L^1(R)$ using a nonharmonic Fourier series. When we construct this series, we have used dyadic subdivision schemes.