• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2009.01a
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• pp.254-257
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• 2009

In this paper, we propose a learning-based super-resolution algorithm. In the proposed algorithm, a multi-resolution wavelet approach is adopted to perform the synthesis of local high-frequency features. To obtain a high-resolution image, wavelet coefficients of two dominant LH- and HL-bands are estimated based on wavelet frames. In order to prepare more efficient training sets, the proposed algorithm utilizes the LH-band and transposed HL-band. The training sets are then used for the estimation of wavelet coefficients for both LH- and HL-bands. Using the estimated high frequency bands, a high resolution image is reconstructed via the wavelet transform. Experimental results demonstrate that the proposed scheme can synthesize high-quality images.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.31B no.12
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• pp.20-26
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• 1994

Lossless system has been employed to design the perfect reconstruction filter banks and has particularly a close relation with the desing of orthogonal wavelet filter (OWF). With such a relation, we generalize 2-band OWF to the M-band OWF which has an improved performances. The improvement is achieved using the two techniques. One is that the wavelet low pass filter has (N-1)th order regularity with extra zeros while the existing filter has N-th order regularity. The other is that unitary matrix is designed by adding the zeros to the proper positions. As a result, M-band OWF designed by propose method has better performance than M-band OWF designed by exsiting method.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.2
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• pp.111-118
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• 2004

A number of researchers have attempted to measure the reverberation time of a passenger car, ut the reverberation time of passenger car is too short to measure with the traditional band pass filter. And if the reverberation time is very short, the product of the reverberation time (T) and the bandwidth (B) of the traditional band pass fitter becomes small. The low limit of BT product required for the measurement of reverberation time with the traditional band pass filter is 16. In order to overcome this problem, the wavelet filter bank was developed. In this study, this new wavelet filter was employed to measure the reverberation times of five different classes of passenger cars. The low limit of BT product required for the measurement of reverberation time with the wavelet filter is 4. The reverberation times of five passenger cars were measured successfully with the new wavelet filter bank. The reverberation times measured in most passenger cars was found to be around 0.04. Compared with general acoustic rooms like concert halls, this is a very short reverberation time

• Journal of Biomedical Engineering Research
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• v.24 no.2
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• pp.99-106
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• 2003

In this paper, a method of discriminating EEG for diagnoses of mental activity is proposed. The proposed method for classification of schizophrenia and normal EEG is based on the wavelet transform and the artificial neural network. The wavelet coefficients of $\alpha$ band, $\beta$ band, $\theta$ band, and $\delta$ band are obtained using the wavelet transform. The magnitude, mean, and variance of wavelet coefficients for each EEG band are applied to the input data of the system's ANN. The architecture of the ANN s a four layered feedforward network with two hidden layer which implements the error back propagation learning algorithm. Through the classification of schizophrenia composed of 19 ANNs corresponding to 19 channels, the classifying system show that it can classify the 100% of the normal EEG group and the 86.67% of the schizophrenia EEG group.

• Journal of information and communication convergence engineering
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• v.9 no.6
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• pp.763-768
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• 2011

Image denoising is a lively research field. Today the researches are focus on the wavelet domain especially using wavelet threshold method. We proposed an adaptive threshold method which considering the characteristic of different sub-band, the method is adaptive to each sub-band. Experiment results show that the proposed method extracts white Gaussian noise from original signals in each step scale and eliminates the noise effectively. In addition, the method also preserves the detail information of the original image, obtaining superior quality image with higher peak signal to noise ratio(PSNR).

• Journal of Mechanical Science and Technology
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• v.17 no.4
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• pp.511-520
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• 2003

In room acoustics, reverberation time is an important acoustic parameter. However it is often difficult to measure short reverberation times at low frequencies with a traditional band pass filter bank if the product of filter bandwidth (B) and reverberation time (T) is small. It it well known that the minimum permissible product of bandwidth and reverberation time of the traditional band pass filter is at least 16. This strict requirement makes it difficult to measure short reverberation times of an acoustic room at low frequencies exactly. In order to reduce this strict requirement, in the previous paper, the wavelet filter bank was developed and the minimum permissible product of bandwidth and reverberation time was replaced with 4. In the present paper it is demonstrated how the short reverberation times of an practical room at low frequencies are successfully measured by using the wavelet filter bank and the results are compared with the traditional method using a band past filer bank.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3028-3030
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• 2000

In general. a speech coding is dedicated to the compression performance or the speech quality. But. the speech coding in this paper is focused on the performance of flexible transmission to the, network speed. For this. the subbanding coding is needed. which is used the wavelet packet concept in the signal analysis. The extraction of each frequency-band is difficult to general signal analysis methods, after coding each band, the reconstruction of these is also a difficult problem. But. with the wavelet packet concept(perfect reconstruction) and its fast computation algorithm. the extraction of each band and the reconstruction are more natural. Also, this paper describes a direct solution of the voice transmission on network and implement this algorithm at the TCP/IP network environment of PC.

• Journal of Information Processing Systems
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• v.17 no.6
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• pp.1170-1178
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• 2021

This paper proposed a versatile algorithm based on a dual-tree complex wavelet transform for intensifying the visual aspect of medical images. First, the decomposition of the input image into a high sub-band and low-sub-band image is done. Further, to improve the resolution of the resulting image, the high sub-band image is interpolated using Lanczos interpolation. Also, contrast enhancement is performed by singular value decomposition (SVD). Finally, the image reconstruction is achieved by using an inverse wavelet transform. Then, the Gaussian filter will improve the visual quality of the image. We have collected images from the hospital and the internet for quantitative and qualitative analysis. These images act as a reference image for comparing the effectiveness of the proposed algorithm with the existing state-of-the-art. We have divided the proposed algorithm into several stages: preprocessing, contrast enhancement, resolution enhancement, and visual quality enhancement. Both analyses show the proposed algorithm's effectiveness compared to existing methods.

• Journal of Ocean Engineering and Technology
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• v.24 no.2
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• pp.53-56
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• 2010

Oil spills and red tide can be very damaging to the environment and fishery farming. These catastrophic accidents must be detected as quickly as possible. In this paper, we report the results of applying the wavelet transform to SAR or marine radar images for the detection of the boundaries of an oil spill or red tide. The application of the wavelet transform to these phenomena looks quite promising in detecting the boundaries of oil spills and red tide areas.

• Journal of Korea Water Resources Association
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• v.38 no.6 s.155
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• pp.439-448
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• 2005

This paper introduces the wavelet transform that was improved by the fourier transform to assess periodicities and trends, we assessed propriety with examples of two monthly precipitation data, annual precipitation, SOI index and SST index. The wavelet transform can effectively assess the power spectrum corresponding to frequency as maintaining chronological characteristics. The results of the analysis using the wavelet transform showed that the monthly precipitation have the strongest power spectrum near that of 1 year, and the annual precipitation represent the dominated spectrum in the band of 2-8 years. Also, the SOI index and SST index indicate the strongest power spectrum in the band of 2-8 years.