• Title/Summary/Keyword: truncated coefficient vector

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A Study on Hilbert Transform Pair of Wavelet using Truncated Coefficient Vector (절단된 계수 벡터를 사용한 웨이브렛의 힐버트 변환쌍에 관한 연구)

  • 배상범;김남호
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.5
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    • pp.1095-1100
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    • 2003
  • The wavelet transform pair used simultaneously when two wavelets are designed to form an approximate Hilbert transform pair provide excellent property than present DWT(discrete wavelet transform), especially in field that detect wide-band signals like pulse and increase the bit rate at the same bandwidth. In this paper, the two dyadic wavelet bases which form an approximate Hilbert transform pair were designed, and flat delay filter which has the truncated coefficient vector is used in order that the two filters can form Hilbert transform relation in the process of design.

A Study on Detecting Impulse noise using Wavelet (웨이브렛을 이용한 임펄스 노이즈 검출에 관한 연구)

  • 배상범;김남호
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2003.05a
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    • pp.431-434
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    • 2003
  • As a wavelet transform which is presented as a new technique of signal processing field has time and frequency localization capabilities, it's possible for multiresolution analysis as well as easy to analyze various signal. So it is being applied in many fields recently. And when two wavelet base were designed to form Hilbert transform pair, wavelet pair show superior performance than the existing DWT(discrete wavelet transform) in data detection of pulse type. Therefore in this paper, we detected position of impulse noise by using two dyadic wavelet base which is designed by truncated coefficient vector.

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A Study on Detecting Position of Impulse Noise using Wavelet Transform Pair (웨이브렛 변환쌍을 이용한 임펄스 노이즈의 위치 검출에 관한 연구)

  • 배상범;류지구;김남호
    • Proceedings of the Korea Institute of Convergence Signal Processing
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    • 2003.06a
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    • pp.284-287
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    • 2003
  • A wavelet transform which is presented as a new technique of signal processing field decompose input signals into subsignals for expressing them in different resolutions and into detail signals for expressing the remaining signals. And the signals obtained from the progress include the information about input signals at the same time and scale. And when two wavelet bases are designed to form Hilbert transform pair, wavelet Pair show superior performance than the existing DWT in data detection of pulse type. Therefore in this paper, we detected position of impulse noise by using two dyadic wavelet bases which are designed by truncated coefficient vector.

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A Study on the Removal of Impulse Noiseusing Wavelet Transform Pair and Adaptive-Length Median filter (웨이브렛 변환쌍과 적응-길이 메디안 필터를 이용한 임펄스 노이즈 제거에 관한 연구)

  • 배상범;김남호
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.7 no.7
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    • pp.1575-1581
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    • 2003
  • As a society has progressed rapidly toward a highly advanced digital information age, a multimedia communication service for acquisition, transmission and storage of image data as well as voice has being commercialized externally and internally. However, in the process of digitalization or transmission of data, noise is generated by several causes, and researches for eliminating those noises have been continued until now. There were the existing FFT(fast fourier transform) and STFT(short time fourier transform) for removing noise but it's impossible to know information about time and time-frequency localization capabilities has conflictive relationship. Therefore, for overcoming these limits, wavelet transform which is presented as a new technique of signal processing field is being applied in many fields recently. Because it has time-frequency localization capabilities it's Possible for multiresolution analysis as well as easy to analyze various signal. And when two wavelet base were designed to form Hilbert transform pair, wavelet pair provide superior performance than the existing DWT(discrete wavelet transform) in data characteristic detection. Therefore in this parer, we removed impulse noise by using adaptive-length median filter and two dyadic wavelet base which is designed by truncated coefficient vector.