• 제목/요약/키워드: Wavelet packet

검색결과 162건 처리시간 0.024초

웨이블렛 패킷 변환을 이용한 디지털 워터마킹 (Digital Watermarking using Wavelet Packet Transform)

  • 추형석;안종구
    • 전기학회논문지
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    • 제57권8호
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    • pp.1478-1483
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    • 2008
  • In this paper, a digital watermarking method using the WPT (Wavelet Packet Transform) is proposed. The proposed algorithm transforms the input image by using the WPT and inserts the watermark by using the quad-tree algorithm and Cox's algorithm. The experiments for evaluating the performances of the proposed algorithm is carried out by inserting a watermark in each wavelet packet transform step and by inserting a watermark into the lowest frequency domain (LL). As a simulation result, the performance of the insertion of the watermark into the 6 levels of WPT is better than that of other cases. In addition, about $30{\sim}60%$ of all watermarks are inserted into the LL band, the correlation value is improved though the PSNR performance decreases $1{\sim}2dB$.

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

  • 이창기;김대익
    • 한국전자통신학회논문지
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    • 제4권3호
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    • pp.190-196
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    • 2009
  • 본 논문은 잡음 환경의 음성 인식을 위하여 음성에 부가된 잡음을 제거하는 방법으로 프레임 단위로 웨이브렛 변환을 하여 웨이브렛 계수의 표준편차를 이용하여 시간 적응 임계값을 정하는 새로운 방법을 제안한다. 음성의 특성을 고려하기 위하여 고주파 성분을 많이 가지는 무성음의 경우는 첫 번째 스케일의 detail 신호에서, 저주파 성분을 많이 가지는 유성음의 경우는 세 번째 스케일의 approximation 신호의 표준편차를 이용하여 시간 적응 임계값을 설정하였다 또한 제안한 방법으로 잡음을 제거한 후에도 묵음구간에 잔여 잡음이 존재하게 되므로 묵음구간을 검출하여 묵음구간의 잔여 잡음을 제거하였다 실험을 통해 제안한 방법이 일반적인 웨이브렛 변환과 웨이브렛 패킷 변환을 이용한 방법보다 SNR과 MSE측면에서 향상됨을 확인 할 수 있었다.

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Speech Noise Cancellation using Time Adaptive Threshold Value in Wavelet Transform

  • Lee Chul-Hee;Lee Ki-Hoon;Hwang Hyang-Ja;Moon In-Seob;Kim Chong-Kyo
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2004년도 ICEIC The International Conference on Electronics Informations and Communications
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    • pp.244-248
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    • 2004
  • This paper proposes a new noise cancellation method for speech recognition in noise environments. We determine the time adaptive threshold value using standard deviations of wavelet coefficients after wavelet transform by frames. The time adaptive threshold value is set up by using sum of standard deviations of wavelet coefficients in cA3 and weighted cD1. cA3 coefficients represent the voiced sound with lower frequency components and cD1 coefficients represent the unvoiced sound with higher frequency components. In experiments, we removed noise after adding white Gaussian noise and colored noise to original speech. The proposed method improved SNR and MSE more than wavelet transform and wavelet packet transform does. As a result of speech recognition experiment using noise speech DB, recognition performance is improved by $2\sim4\;\%.$

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무손실.손실 영상 압축을 위한 웨이브릿 기반 알고리즘에 관한 연구 (A Study on the Wavelet Based Algorithm for Lossless and Lossy Image Compression)

  • 안종구;추형석
    • 대한전기학회논문지:시스템및제어부문D
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    • 제55권3호
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    • pp.124-130
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    • 2006
  • A wavelet-based image compression system allowing both lossless and lossy image compression is proposed in this paper. The proposed algorithm consists of the two stages. The first stage uses the wavelet packet transform and the quad-tree coding scheme for the lossy compression. In the second stage, the residue image taken between the original image and the lossy reconstruction image is coded for the lossless image compression by using the integer wavelet transform and the context based predictive technique with feedback error. The proposed wavelet-based algorithm, allowing an optional lossless reconstruction of a given image, transmits progressively image materials and chooses an appropriate wavelet filter in each stage. The lossy compression result of the proposed algorithm improves up to the maximum 1 dB PSNR performance of the high frequency image, compared to that of JPEG-2000 algorithm and that of S+P algorithm. In addition, the lossless compression result of the proposed algorithm improves up to the maximum 0.39 compression rates of the high frequency image, compared to that of the existing algorithm.

웨이브렛 패킷 기반 캡스트럼 계수를 이용한 수중 천이신호 특징 추출 알고리즘 (Feature Extraction Algorithm for Underwater Transient Signal Using Cepstral Coefficients Based on Wavelet Packet)

  • 김주호;팽동국;이종현;이승우
    • 한국해양공학회지
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    • 제28권6호
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    • pp.552-559
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    • 2014
  • In general, the number of underwater transient signals is very limited for research on automatic recognition. Data-dependent feature extraction is one of the most effective methods in this case. Therefore, we suggest WPCC (Wavelet packet ceptsral coefficient) as a feature extraction method. A wavelet packet best tree for each data set is formed using an entropy-based cost function. Then, every terminal node of the best trees is counted to build a common wavelet best tree. It corresponds to flexible and non-uniform filter bank reflecting characteristics for the data set. A GMM (Gaussian mixture model) is used to classify five classes of underwater transient data sets. The error rate of the WPCC is compared using MFCC (Mel-frequency ceptsral coefficients). The error rates of WPCC-db20, db40, and MFCC are 0.4%, 0%, and 0.4%, respectively, when the training data consist of six out of the nine pieces of data in each class. However, WPCC-db20 and db40 show rates of 2.98% and 1.20%, respectively, while MFCC shows a rate of 7.14% when the training data consists of only three pieces. This shows that WPCC is less sensitive to the number of training data pieces than MFCC. Thus, it could be a more appropriate method for underwater transient recognition. These results may be helpful to develop an automatic recognition system for an underwater transient signal.

인지 모델과 웨이블릿 패킷 변환을 이용한 잡음 제거기 설계 (Design of the Noise Suppressor Using the Perceptual Model and Wavelet Packet Transform)

  • 김미선;박서영;김영주;이인성
    • 한국음향학회지
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    • 제25권7호
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    • pp.325-332
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    • 2006
  • 본 논문은 인지 모델과 웨이블릿 패킷 변환을 이용하여 단일 채널에서 유색잡음 또는 비정지적 성격의 잡음을 제거하는데 목적을 두고 있다. 이러한 잡음은 부대역을 나누어 접근해야하며, 잔여잡음과 음성의 왜곡으로 인한 문제를 해결하기 위해 웨이블릿 패킷 변환 후 웨이블릿 계수 문턱값을 적절히 개선해야 한다. 본 논문에서 부대역은 웨이블릿 패킷변환 후에 스케일과 임계대역을 매칭하여 설계하였으며, 웨이블릿 계수 문턱값은 세그멘탈 신호대잡음비 (seg_SNR)와 노이즈마스킹 임계값 (Noise Masking Threshold W)을 이용하여 적응적으로 계산했다. 결과적으로 TTA 표준인 EVRC 잡음 제거기와 유사한 성능을 가졌으며, 웨이블릿 변환 후 웨이블릿 계수에 Universal 문턱값을 적용하는 것보다 PESQ-MOS 값이 0.29 높았다. 인코딩과 디코딩 후 PESQ-MOS 값은 EVRC 잡음 제거기보다 0.23 정도 우수한 성능을 가졌다.

부대역 에너지 기반 웨이블릿 패킷 변환을 이용한 인증을 위한 세미 프레자일 영상 워터마킹 (Semi-Fragile Image Watermarking for Authentication Using Wavelet Packet Transform Based on The Subband Energy)

  • 박상주;권태현
    • 정보처리학회논문지B
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    • 제12B권4호
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    • pp.421-428
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    • 2005
  • 디지털 영상 데이터의 인증을 주장하기 위한 세미 프래자일 워터마크를 제안한다. 각 부대역들의 에너지 크기에 기반하는 적응적인 웨이블릿 패킷 분해된 디지털 영상의 특정 중간 주파수 영역의 변환 계수에 양자화 잡음의 형태로 워터마크 정보를 삽입한다. 워터마크의 강도는 인간의 시각인지 특성을 이용하여 조절함으로써, 쉽게 인지되지 않으면서도 영상의 정보/저장에 필요한 압축 등과 같은 비고의적 변형에 강인한 특성을 갖는다. 원본 영상에 공격이 가해진 경우, 공격 위치의 웨이블릿 변환 계수뿐 아니라 주위의 계수 값들도 변형될 가능성이 높다. 따라서 인증을 위한 방법으로는 현재 변환 계수와 주변의 계수들의 훼손 여부를 함께 고려하였다. 원본 영상의 훼손 여부를 효율적으로 판단할 수 있고 훼손된 위치도 정밀하게 파악할 수 있다. 응용 분야에 따라 판단 임계값은 사용자가 필요에 따라 설정할 수 있다.

필터 설계 기법을 통한 WPM의 PAPR 감소에 관한 연구 (PAPR Reduction for WPM Schemes using Filter Design Schemes)

  • 이규섭;최진규
    • 한국인터넷방송통신학회논문지
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    • 제13권1호
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    • pp.49-54
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    • 2013
  • WPM(Wavelet Packet Modulation)은 고속 전송에 적합한 다중 반송파 전송방식으로 여러 필터의 조합으로 유연한 시스템을 구현할 수 있는 장점이 있다. WPM과 같은 다중 반송파 시스템에서 높은 PAPR(Peak to Average Power Ratio)은 가장 큰 문제점중 하나이다. 본 논문에서는 WPM 시스템의 필터 계수를 조정 하는 방법으로 최소 PAPR을 갖는 WPM 시스템을 제안한다. 우선 PR(Perfect Reconstruction)을 만족하는 필터 계수의 방정식을 구하여 그 방정식을 이용하여 PAPR이 가장 낮게 나올 수 있는 필터계수를 선택한다. 이 필터 계수를 이용하여 최소 PAPR을 갖는 WPM 시스템을 구현하고 모의실험을 통하여 성능 비교를 하였다.

Improved Decoupled Control and Islanding Detection of Inverter-Based Distribution in Multibus Microgrid Systems

  • Pinto, Smitha Joyce;Panda, Gayadhar
    • Journal of Power Electronics
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    • 제16권4호
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    • pp.1526-1540
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    • 2016
  • This work mainly discusses an accurate and fast islanding detection based on fractional wavelet packet transform (FRWPT)for multibus microgrid systems. The proposed protection scheme uses combined desirable features retrieved from discrete fractional Fourier transform (FRFT) and wavelet packet transform (WPT) techniques, which provides precise time-frequency information on minute perturbation signals introduced in the system. Moreover, this study focuses on the design of decoupling control with a distributed controller based on state feedback for the efficient operation of microgrid systems that are transitioning from the grid-connected mode to the islanded mode. An IEEE 9-bus test system with inverter based distributed generation (DG) units is considered for islanding assessment and smooth operation. Finally, tracking errors are greatly reduced with stability improvement based on the proposed controller. FRWPT based islanding detection is demonstrated via a time domain simulation of the system. Simulated results show an improvement in system stability with the application of the proposed controller and accurate islanding detection based on the FRWPT technique in comparison with the results obtained by applying the wavelet transform (WT) and WPT.

A statistical reference-free damage identification for real-time monitoring of truss bridges using wavelet-based log likelihood ratios

  • Lee, Soon Gie;Yun, Gun Jin
    • Smart Structures and Systems
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    • 제12권2호
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    • pp.181-207
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    • 2013
  • In this paper, a statistical reference-free real-time damage detection methodology is proposed for detecting joint and member damage of truss bridge structures. For the statistical damage sensitive index (DSI), wavelet packet decomposition (WPD) in conjunction with the log likelihood ratio was suggested. A sensitivity test for selecting a wavelet packet that is most sensitive to damage level was conducted and determination of the level of decomposition was also described. Advantages of the proposed method for applications to real-time health monitoring systems were demonstrated by using the log likelihood ratios instead of likelihood ratios. A laboratory truss bridge structure instrumented with accelerometers and a shaker was used for experimental verification tests of the proposed methodology. The statistical reference-free real-time damage detection algorithm was successfully implemented and verified by detecting three damage types frequently observed in truss bridge structures - such as loss of bolts, loosening of bolts at multiple locations, sectional loss of members - without reference signals from pristine structure. The DSI based on WPD and the log likelihood ratio showed consistent and reliable results under different damage scenarios.