• Title/Summary/Keyword: wavelet representation

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Error Concealment Based on Multiple Representation for Wireless Transmission of JPEG2000 Image

  • Ou, Yang;Lee, Won-Young;Yang, Tae-Uk;Chee, Sung-Taek;Rhee, Kyung-Hyune
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.1C
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    • pp.68-78
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    • 2008
  • The transmission of multimedia information over error-prone channels such as wireless networks has become an important area of research. In this paper, we propose two Error Concealment(EC) schemes for wireless transmission of JPEG2000 image. The Multiple Representation(MR) is employed as the preprocessing in our schemes, whereas the main error concealing operation is applied in wavelet domain at receiver side. The compressed code-stream of several subsampled versions of original image is transmitted over a single channel with random bit errors. In the decoder side, the correctly reconstructed wavelet coefficients are utilized to recover the corrupted coefficients in other sub-images. The recovery is carried out by proposed basic(MREC-BS) or enhanced(MREC-ES) methods, both of which can be simply implemented. Moreover, there is no iterative processing during error concealing, which results a big time saving. Also, the simulation results confirm the effectiveness and efficiency of our proposed schemes.

Hybrid DCT/DFflWavelet Architecture Based on Jacket Matrix

  • Chen, Zhu;Lee, Moon-Ho
    • Proceedings of the KIEE Conference
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    • 2007.04a
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    • pp.281-282
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    • 2007
  • We address a new representation of DCT/DFT/Wavelet matrices via one hybrid architecture. Based on an element inverse matrix factorization algorithm, we show that the OCT, OFT and Wavelet which based on Haar matrix have the similarrecursive computational pattern, all of them can be decomposed to one orthogonal character matrix and a special sparse matrix. The special sparse matrix belongs to Jacket matrix, whose inverse can be from element-wise inverse or block-wise inverse. Based on this trait, we can develop a hybrid architecture.

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The study of New Compression method using Contourlet transform (Contourlet 변환을 이용한 새로운 압축방법에 대한 연구)

  • Chong, Hyun-Jin;Jang, Jun-Ho;Kim, Young-Seop
    • Journal of the Semiconductor & Display Technology
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    • v.6 no.3
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    • pp.55-59
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    • 2007
  • Wavelet Transform is amenable to efficient algorithms. So wavelet transform was adopted many signal processing and communication applications. For example, the wavelet transform was adopted as the transform for JPEG2000. However, Wavelet has weakness about smoothness along the contours and limited directional information. Hence, recently, some new transforms have been introduced to take advantage of this property. So we use to other transform, called contourlet transform in compression. In this paper, we propose a new method for image compression based on the contourlet transform, which has been recently introduced. Contourlet transform has a good result about images with smooth contours. Moreover, Contourlet is feasible multiresolution and multidirection expansion using non-separable filter bank. This treatise shows a good image representation after compressing using contourlet transform.

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An Application of k-domain Discrete Wavelet Transform for the Efficient Representation of Green Function (파수영역 이산 웨이블릿 변환을 이용한 효율적인 그린함수 표현에 관한 연구)

  • 주세훈;김형동
    • The Journal of Korean Institute of Electromagnetic Engineering and Science
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    • v.12 no.7
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    • pp.1110-1114
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    • 2001
  • The discrete wavelet concept in the k-domain is applied to efficiently represent Green function of integral equations. Application of discrete wavelet concept to Green function in the k-domain can be implemented equivalently by using spatial domain variable-sized windows. The proposed method consists of constant Q-filtering, changing the center of coordinates, and transforming spatially filtered Green functions into those in the k-domain. A mathematical expression of Green function based on the discrete wavelet concept is derived and its characteristics are discussed.

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COMPACTLY SUPPORTED WAVELET AND THE NUMERICAL SOLUTION OF THE VLASOV EQUATION

  • Benhadid, Yacine
    • Journal of applied mathematics & informatics
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    • v.24 no.1_2
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    • pp.17-30
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    • 2007
  • A new scheme for solving the Vlasov equation using a compactly supported wavelets basis is proposed. We use a numerical method which minimizes the numerical diffusion and conserves a reasonable time computing cost. So we introduce a representation in a compactly supported wavelet of the derivative operator. This method makes easy and simple the computation of the coefficients of the matrix representing the operator. This allows us to solve the two equations which result from the splitting technique of the main Vlasov equation. Some numerical results are exposed using different numbers of wavelets.

Sparse Point Representation Based on Interpolation Wavelets (보간 웨이블렛 기반의 Sparse Point Representation)

  • Park, Jun-Pyo;Lee, Do-Hyung;Maeng, Joo-Sung
    • Transactions of the Korean Society of Mechanical Engineers B
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    • v.30 no.1 s.244
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    • pp.8-15
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    • 2006
  • A Sparse Point Representation(SPR) based on interpolation wavelets is presented. The SPR is implemented for the purpose of CFD data compression. Unlike conventional wavelet transformation, the SPR relieves computing workload in the similar fashion of lifting scheme that includes splitting and prediction procedures in sequence. However, SPR skips update procedure that is major part of lifting scheme. Data compression can be achieved by proper thresholding method. The advantage of the SPR method is that, by keeping even point physical values, low frequency filtering procedure is omitted and its related unphysical thresholing mechanism can be avoided in reconstruction process. Extra singular feature detection algorithm is implemented for preserving singular features such as shock and vortices. Several numerical tests show the adequacy of SPR for the CFD data. It is also shown that it can be easily extended to nonlinear adaptive wavelets for enhanced feature capturing.

Simulation of multivariate non-Gaussian wind pressure on spherical latticed structures

  • Aung, Nyi Nyi;Ye, Jihong;Masters, F.J.
    • Wind and Structures
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    • v.15 no.3
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    • pp.223-245
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    • 2012
  • Multivariate simulation is necessary for cases where non-Gaussian processes at spatially distributed locations are desired. A simulation algorithm to generate non-Gaussian wind pressure fields is proposed. Gaussian sample fields are generated based on the spectral representation method using wavelet transforms method and then mapped into non-Gaussian sample fields with the aid of a CDF mapping transformation technique. To illustrate the procedure, this approach is applied to experimental results obtained from wind tunnel tests on the domes. A multivariate Gaussian simulation technique is developed and then extended to multivariate non-Gaussian simulation using the CDF mapping technique. It is proposed to develop a new wavelet-based CDF mapping technique for simulation of multivariate non-Gaussian wind pressure process. The efficiency of the proposed methodology for the non-Gaussian nature of pressure fluctuations on separated flow regions of different rise-span ratios of domes is also discussed.

Synchrosqueezed wavelet transform for frequency and damping identification from noisy signals

  • Montejo, Luis A.;Vidot-Vega, Aidcer L.
    • Smart Structures and Systems
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    • v.9 no.5
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    • pp.441-459
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    • 2012
  • Identification of vibration parameters from the analysis of the dynamic response of a structure plays a key role in current health monitoring systems. This study evaluates the capabilities of the recently developed Synchrosqueezed Wavelet Transform (SWT) to extract instant frequencies and damping values from the simulated noise-contaminated response of a structure. Two approaches to estimate the modal damping ratio from the results of the SWT are presented. The results obtained are compared to other signal processing methods based on Continuous Wavelet (CWT) and Hilbert-Huang (HHT) transforms. It was found that the time-frequency representation obtained via SWT is sharped than the obtained using just the CWT and it allows a more robust extraction of the individual modal responses than using the HHT. However, the identification of damping ratios is more stable when the CWT coefficients are employed.

A Lossless and Lossy Audio Compression using Prediction Model and Wavelet Transform

  • Park, Se-Yil;Park, Se-Hyoung;Lim, Dae-Sik;Jaeho Shin
    • Proceedings of the IEEK Conference
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    • 2002.07c
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    • pp.2063-2066
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    • 2002
  • In this paper, we propose a structure far lossless audio coding method. Prediction model is used in the wavelet transform domain. After DWT, wavelet coefficients is quantized and decorrelated by prediction modeling. The DWT can be constructed to critical bands. We can get a lower data rate representation of audio signal which has a good quality like the result of perceptual coding. Then the prediction errors are efficiently coded by the Golomb-coding method. The prediction coefficients are fixed for reducing the computational burden when we find prediction coefficients.

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A NUMBER SYSTEM IN ℝn

  • Jeong, Eui-Chai
    • Journal of the Korean Mathematical Society
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    • v.41 no.6
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    • pp.945-955
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    • 2004
  • In this paper, we establish a number system in $R^n$ which arises from a Haar wavelet basis in connection with decompositions of certain Cuntz algebra representations on $L^2$( $R^n$). Number systems in $R^n$ are also of independent interest [9]. We study radix-representations of $\chi$ $\in$ $R^n$: $\chi$:$\alpha$$_{ι}$ $\alpha$$_{ι-1}$$\alpha$$_1$$\alpha$$_{0}$$\alpha$$_{-1}$ $\alpha$$_{-2}$ … as $\chi$= $M^{ι}$$\alpha$$_{ι}$ $\alpha$+…M$\alpha$$_1$$\alpha$$_{0}$$M^{-1}$ $\alpha$$_{-1}$$M^{-2}$ $\alpha$$_{-2}$ +… where each $\alpha$$_{k}$ $\in$ D, and D is some specified digit set. Our analysis uses iteration techniques of a number-theoretic flavor. The view-point is a dual one which we term fractals in the large vs. fractals in the small,illustrating the number theory of integral lattice points vs. fractions.s vs. fractions.