• Title/Summary/Keyword: transform coefficients

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Adaptive Noise Reduction using Standard Deviation of Wavelet Coefficients in Speech Signal (웨이브렛 계수의 표준편차를 이용한 음성신호의 적응 잡음 제거)

  • 황향자;정광일;이상태;김종교
    • Science of Emotion and Sensibility
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    • v.7 no.2
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    • pp.141-148
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    • 2004
  • This paper proposed a new time adapted threshold using the standard deviations of Wavelet coefficients after Wavelet transform by frame scale. The time adapted threshold is set up using the sum of standard deviations of Wavelet coefficient in cA3 and weighted cDl. cA3 coefficients represent the voiced sound with low frequency and cDl coefficients represent the unvoiced sound with high frequency. From simulation results, it is demonstrated that the proposed algorithm improves SNR and MSE performance more than Wavelet transform and Wavelet packet transform does. Moreover, the reconstructed signals by the proposed algorithm resemble the original signal in terms of plosive sound, fricative sound and affricate sound but Wavelet transform and Wavelet packet transform reduce those sounds seriously.

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Adaptive Noise Reduction of Speech Using Wavelet Transform (웨이브렛 변환을 이용한 음성의 적응 잡음 제거)

  • Lee, Chang-Ki;Kim, Dae-Ik
    • The Journal of the Korea institute of electronic communication sciences
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    • v.4 no.3
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    • pp.190-196
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    • 2009
  • A new time adapted threshold using the standard deviations of Wavelet coefficients after Wavelet transform by frame scale is proposed. The time adapted threshold is set up using the sum of standard deviations of Wavelet coefficient in level 3 approximation and weighted level 1 detail. Level 3 approximation coefficients represent the voiced sound with low frequency and level 1 detail coefficients represent the unvoiced sound with high frequency. After reducing noise by soft thresholding with the proposed time adapted threshold, there are still residual noises in silent interval. To reduce residual noises in silent interval, a detection algorithm of silent interval is proposed. From simulation results, it can be noticed that SNR and MSE of the proposed algorithm are improved than those of Wavelet transform and than those of Wavelet packet transform.

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Adaptive Noise Reduction of Speech using Wavelet Transform (웨이브렛 변환을 이용한 음성의 적응 잡음 제거)

  • Im Hyung-kyu;Kim Cheol-su
    • Journal of the Korea Computer Industry Society
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    • v.6 no.2
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    • pp.271-278
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    • 2005
  • This paper proposed a new time adapted threshold using the standard deviations of Wavelet coefficients after Wavelet transform by frame scale. The time adapted threshold is set up using the sum of standard deviations of Wavelet coefficient in level 3 approximation and weighted level 1 detail. Level 3 approximation coefficients represent the voiced sound with low frequency and level 1 detail coefficients represent the unvoiced sound with high frequency. After reducing noise by soft thresholding with the proposed time adapted threshold, there are still residual noises in silent interval. To reduce residual noises in silent interval, a detection algorithm of silent interval is proposed. From simulation results, it is demonstrated that the proposed algorithm improves SNR and MSE performance more than Wavelet transform and Wavelet packet transform does.

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A Study on Auto-Classification of Acoustic Emission Signals Using Wavelet Transform and Neural Network (웨이블렛 변환과 신경망을 이용한 음향방출신호의 자동분류에 관한연구)

  • Park, Jae-Jun;Kim, Meyoun-Soo;Oh, Seung-Heon;Kang, Tae-Rim;Kim, Sung-Hong;Beak, Kwan-Hyun;Oh, Il-Duck;Song, Young-Chul;Kwon, Dong-Jin
    • Proceedings of the KIEE Conference
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    • 2000.07c
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    • pp.1880-1884
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    • 2000
  • The discrete wavelet transform is utilized as preprocessing of Neural Network(NN) to identify aging state of internal partial discharge in transformer. The discrete traveler transform is used to produce wavelet coefficients which are used for Classification. The statistical parameters (maximum of wavelet coefficients, average value, dispersion, skewness, kurtosis) using the wavelet coefficients are input into an back-propagation neural network. The neurons whose weights have obtained through Result of Cross-Validation. The Neural Network learning stops either when the error rate achieves an appropriate minimum or when the learning time overcomes a constant value. The networks, after training, can decide if the test signal is Early Aging State or Last Aging State or normal state.

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Adaptive Image Coding Technique using HVS in Biorthogonal Wavelet Transform Domain (Biorthogonal 웨이브릿 변환영역에서 HVS를 이용한 적응 영상 부호화 기법)

  • 김응태;김형명
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.18 no.10
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    • pp.1469-1482
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    • 1993
  • A new image coding technique has been proposed based on the wavelet transform. To achieve lower ceding rates and good qualities in reconstructed images, some of wavelet coefficients were removed by thresholding and quantized in accordance with the sensitivity of the human visual system(HVS). For each block of subimages in wavelet transform domain, block thresholding scheme has been used to remove the unimportant wavelet coefficients according to the frequency characteristic and statistical property of wavelet coefficients. The location information of quantized blocks and removed blocks were encoded using run-length coder which is effective for the exponential distribution. Quantized coefficients were encoded using variable length coder which matches well to their distribution. Simulation results show that the reconstructed images maintain high quality with the low bit rate, below 1.0 bits per pel.

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Detection of delamination damage in composite beams and plates using wavelet analysis

  • Bombale, B.S.;Singha, M.K.;Kapuria, S.
    • Structural Engineering and Mechanics
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    • v.30 no.6
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    • pp.699-712
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    • 2008
  • The effectiveness of wavelet transform in detecting delamination damages in multilayered composite beams and plates is studied here. The damaged composite beams and plates are modeled in finite element software ABAQUS and the first few mode shapes are obtained. The mode shapes of the damaged structures are then wavelet transformed. It is observed that the distribution of wavelet coefficients can identify the damage location of beams and plates by showing higher values of wavelet coefficients at the position of damage. The effectiveness of the method is studied for different boundary conditions, damage location and size for single as well as multiple delaminations in composite beams and plates. It is observed that both discrete wavelet transform (DWT) and continuous wavelet transform (CWT) can detect the presence and location of the damaged region from the mode shapes of the structures. DWT may be used to approximately evaluate the size of the delamination area, whereas, CWT is efficient to detect smaller delamination areas in composites.

A Study on Feature Extraction of Transformers Aging Signal using discrete Wavelet Transform Technique (이산 웨이블렛 변환 기법을 이용한 변압기 열화신호의 특징추출에 관한 연구)

  • Park, Jae-Jun;Kwon, Dong-Jin;Song, Yeong-Cheol;Ahn, Chang-Beom
    • The Transactions of the Korean Institute of Electrical Engineers C
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    • v.50 no.3
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    • pp.121-129
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    • 2001
  • In this paper, a new efficient feature extraction method based on Daubechies discrete wavelet transform is presented. This paper especially deals with the assessment of process statistical parameter using the features extracted from the wavelet coefficients of measured acoustic emission signals. Since the parameter assessment using all wavelet coefficients will often turn out leads to inefficient or inaccurate results, we selected that level-3 stage of multi decomposition in discrete wavelet transform. We make use of the feature extraction parameter namely, maximum value of acoustic emission signal, average value, dispersion, skewness, kurtosis, etc. The effectiveness of this new method has been verified on ability a diagnosis transformer go through feature extraction in stage of aging(the early period, the middle period, the last period)

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Diagnosis of Transform Aging using Discrete Wavelet Analysis and Neural Network (이산 웨이블렛 분석과 신경망을 이용한 변압기 열화의 전단)

  • 박재준;윤만영;오승헌;김진승;김성홍;백관현;송영철;권동진
    • Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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    • 2000.07a
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    • pp.645-650
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    • 2000
  • The discrete wavelet transform is utilized as processing of neural network(NN) to identifying aging state of internal partial discharge in transformer. The discrete wavelet transform is used to produce wavelet coefficients which are used for classification. The mean values of the wavelet coefficients are input into an back-propagation neural network. The networks, after training, can decide if the test signals is aging early state or aging last state, or normal state.

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A comparative study of transform coding methods for Image compression (영상 압축을 위한 변환 부호화 방식의 비교 연구)

  • Cho, Soon-Kyui;Yang, Seung-In
    • Proceedings of the KIEE Conference
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    • 1988.07a
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    • pp.222-224
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    • 1988
  • In this paper, the transform coding method was selected out of image compression techniques. Each characteristic of transform coefficients for five transform(DCT, DST, WHT, HAT, SLT) was observed, and their performances were compared and reviewed, based on the results from the experiment where image samples were applied to five transform. As the result of image processing experiment, DCT was found to have the best performance.

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Robust Digital Watermarking for High-definition Video using Steerable Pyramid Transform, Two Dimensional Fast Fourier Transform and Ensemble Position-based Error Correcting

  • Jin, Xun;Kim, JongWeon
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.12 no.7
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    • pp.3438-3454
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    • 2018
  • In this paper, we propose a robust blind watermarking scheme for high-definition video. In the embedding process, luminance component of each frame is transformed by 2-dimensional fast Fourier transform (2D FFT). A secret key is used to generate a matrix of random numbers for the security of watermark information. The matrix is transformed by inverse steerable pyramid transform (SPT). We embed the watermark into the low and mid-frequency of 2D FFT coefficients with the transformed matrix. In the extraction process, the 2D FFT coefficients of each frame and the transformed matrix are transformed by SPT respectively, to produce two oriented sub-bands. We extract the watermark from each frame by cross-correlating two oriented sub-bands. If a video is degraded by some attacks, the watermarks of frames contain some errors. Thus, we use an ensemble position-based error correcting algorithm to estimate the errors and correct them. The experimental results show that the proposed watermarking algorithm is imperceptible and moreover is robust against various attacks. After embedding 64 bits of watermark into each frame, the average peak signal-to-noise ratio between original frames and embedded frames is 45.7 dB.