• 제목/요약/키워드: Wavelet transform

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Quadtree Based Infrared Image Compression in Wavelet Transform Domain (웨이브렛 변환 영역에서 쿼드트리 기반 적외선 영상 압축)

  • 조창호;이상효
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.3C
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    • pp.387-397
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    • 2004
  • The wavelet transform providing both of the frequency and spatial information of an image is proved to be very much effective for the compression of images, and recently lot of studies on coding algorithms for images decomposed by the wavelet transform together with the multi-resolution theory are going on. This paper proposes a quadtree decomposition method of image compression applied to the images decomposed by wavelet transform by using the correlations between pixels and '0'data grouping. Since the coefficients obtained by the wavelet transform have high correlations between scales and high concentrations, the quadtree method can reduce the data quantity effectively. the experimental infrared image with 256${\times}$256 size and 8〔bit〕, was used to compare the performances of the existing and the proposed compression methods.

Image restoration based on wavelet filter bank (웨이블렛 필터 뱅크를 이용한 영상복원)

  • 김주헌;이종수
    • 제어로봇시스템학회:학술대회논문집
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    • 1997.10a
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    • pp.1387-1390
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    • 1997
  • In this paper we propose a novel way to restore degraded image using wavelet transform & filterbank. First, we devide a degraded image into 4-suband images using UDWT(Undecimated Wavelet Transform), and then use a proper CLS (Constrained Least Square) filter in each subband. Using a proper CLS filter ineach subband, we can save high grequency components of original image. We reconstruct a restored image from the downsampled subband images using wavelet tansform. Even though there is a trade-off between ISNR and calculation loads, we reduce the calculation loads by using wavelet transform in reconstruction with a negligible degradatiion in ISNR.

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A Neural Network Based Handwritten-Charater Recognition using Binary Wavelet Transform (이진 웨이브렛 변환을 이용한 신경회로망의 필기체 문자 인식)

  • Lee, Jung-Moon;You, Kyoung-San
    • Journal of Industrial Technology
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    • v.17
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    • pp.331-338
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    • 1997
  • In this paper, we propose a new neural pattern recognition from wavelet transform. We first analysis in BFT(Binary Field Transform) in character image. The proposed neural network and wavelet transform is able to improve learning time and scaling. The ability and effectiveness of identifying image using the proposed wavelet transform will be demonstrated by computer simulation.

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Analysis of Heart Sound Using the Wavelet Transform (Wavelet Transform을 이용한 Heart Sound Analysis)

  • 위지영;김중규
    • Proceedings of the IEEK Conference
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    • 2000.09a
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    • pp.959-962
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    • 2000
  • A heart sound algorithm, which separates the heart sound signal into four parts; the first heart sound, the systolic period, the second heart sound, and the diastolic period has been developed. The algorithm uses discrete intensity envelopes of approximations of the wavelet transform analysis method to the phonocard-iogram(PCG)signal. Heart sound a highly nonstation-ary signal, so in the analysis of heart sound, it is important to study the frequency and time information. Further more, Wavelet Transform provides more features and characteristics of the PCG signal that will help physician to obtain qualitative and quantitative measurements of the heart sound.

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Computationally efficient wavelet transform for coding of arbitrarily-shaped image segments

  • 강의성;이재용;김종한;고성재
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.22 no.8
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    • pp.1715-1721
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    • 1997
  • Wavelet transform is not applicable to arbitrarily-shaped region (or object) in images, due to the nature of its global decomposition. In this paper, the arbitrarily-shaped wavelet transform(ASWT) is proposed in order to solve this problem and its properties are investigated. Computation complexity of the ASWT is also examined and it is shown that the ASWT requires significantly fewer computations than conventional wavelet transform, since the ASWT processes only the object region in the original image. Experimental resutls show that any arbitrarily-shaped image segment can be decomposed using the ASWT and perfectly reconstructed using the inverse ASWT.

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Identification of Abnormal Compressor using Wavelet Transform (Wavelet 변환에 의한 압축기의 이상상태 식별)

  • 정지홍;이기용;김정석;이감규
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1995.10a
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    • pp.361-364
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    • 1995
  • Wavelet Transform is a new tools for signal processing, such as data compressing extraction of parameter for Reconition and Diagnostics. This transform has an advandage of a good resolution compared to Fast Fourier Transform (FFT) In this study, we employ the wavelet transform for analysis of Acoustic Emission raw signal generated form rotary compressor. In abnormal condition of rotary compressor, the state of operating condition can be classified by analizing coefficient of wavelet transformed signal.

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Fast Solution of Linear Systems by Wavelet Transform

  • Park, Chang-Je;Cho, Nam-Zin
    • Proceedings of the Korean Nuclear Society Conference
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    • 1996.05a
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    • pp.282-287
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    • 1996
  • We. develop in this study a wavelet transform method to apply to the flux reconstruction problem in reactor analysis. When we reconstruct pinwise heterogeneous flux by iterative methods, a difficulty arises due to the near singularity of the matrix as the mesh size becomes finer. Here we suggest a wavelet transform to tower the spectral radius of the near singular matrix and thus to converge by a standard iterative scheme. We find that the spectral radios becomes smatter than one after the wavelet transform is performed on sample problems.

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Super-resolution Algorithm using Discrete Wavelet Transform for Single-image (이산 웨이블릿 변환을 이용한 영상의 초고해상도 기법)

  • Lim, Jong-Myeong;Yoo, Ji-Sang
    • Journal of Broadcast Engineering
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    • v.17 no.2
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    • pp.344-353
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    • 2012
  • In this paper, we propose a super-resolution algorithm using discrete wavelet transform. In general super-resolution algorithms for single-image, probability based operations have been used for searching high-frequency components. Consequently, the complexity of the algorithm causes the increase of processing time. In the proposed algorithm, we use discrete wavelet transform to find high-frequency sub-bands. We perform inverse discrete wavelet transform using input image and high-frequency sub-bands of the same resolution as the input image which are obtained by performing discrete wavelet transform without down-sampling and then we obtain image with high-resolution. In the proposed algorithm, we use the down-sampled version of the original image ($512{\times}512$) as a test image ($256{\times}256$) to compare the performance of algorithms. Through experimental results, we confirm the improved efficiency of the proposed algorithm comparing with conventional interpolation algorithms and also decreased processing time comparing the probability based operations.

An Improved Detection Technique for Voltage Sag using the Wavelet Transform

  • Kim, Chul-Hwan;Lee, Jong-Po;Ahn, Sang-Pil;Kim, Byung-Chun
    • KIEE International Transactions on Power Engineering
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    • v.11A no.4
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    • pp.1-8
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    • 2001
  • This paper presents a discrete wavelet transform approach for detecting voltage sags initialized by fault conditions and starting of larger motors. The proposed technique is based on utilizing the summation value of D1(at scale 1) coefficients in multiresolution analysis(MRA) based on the discrete wavelet transform. In this paper, the proposed technique is tested under various cases of voltage sags. It is shown that the voltage sag detection technique based on the wavelet transform is a satisfactory and reliable method for detecting voltage sags in power quality disturbance analysis.

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A Novel Detection Technique for Voltage Sag in Distribution Lines Using the Wavelet Transform

  • Ko, Young-Hun;Kim, Chul-Hwan;Ahn, Sang-Pil
    • KIEE International Transactions on Power Engineering
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    • v.3A no.3
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    • pp.130-138
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    • 2003
  • This paper presents a discrete wavelet transform approach for determining the beginning and end times of voltage sags. Firstly, investigations in the use of some typical mother wavelets, namely Daubechies, Symlets, Coiflets and Biorthogonal are carried out and the most appropriate mother wavelet is selected. The proposed technique is based on utilizing the maximum value of Dl (at scale 1) coefficients in multiresolution analysis (MRA) based on the discrete wavelet transform. The results are compared with other methods for determining voltage sag duration, such as the Root Mean Square (RMS) voltage and Short Time Fourier Transform (STFT) methods. It is shown that the voltage sag detection technique based on the wavelet transform is a satisfactory and reliable method for detecting voltage sags in power quality disturbance analysis.