• Title/Summary/Keyword: 웨이블렛변환

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Image Mosaic using Multiresolution Wavelet Analysis (다해상도 웨이블렛 분석 기법을 이용한 영상 모자이크)

  • Yang, In-Tae;Oh, Myung-Jin;Lee, In-Yeub
    • Journal of Korean Society for Geospatial Information Science
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    • v.12 no.2 s.29
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    • pp.61-66
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    • 2004
  • By the advent of the high-resolution Satellite imagery, there are increasing needs in image mosaicking technology which can be applied to various application fields such as GIS(Geographic Information system). To mosaic images, various methods such as image matching and histogram modification are needed. In this study, automated image mosaicking is performed using image matching method based on the multi-resolution wavelet analysis(MWA). Specifically, both area based and feature based matching method are embedded in the multi-resolution wavelet analysis to construct seam line.; seam points are extracted then polygon clipping method are applied to define overlapped area of two adjoining images. Before mosaicking, radiometric correction is proceeded by using histogram matching method. As a result, mosaicking area is automatically extracted by using polygon clipping method. Also, seamless image is acquired using multi-resolution wavelet analysis.

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Face Recognition Using Wavelet Coefficients and Hidden Markov Model (웨이블렛 계수와 Hidden Markov Model을 이용한 얼굴인식 기법)

  • Lee, Kyung-Ah;Lee, Dae-Jong;Park, Jang-Hwan;Chun, Myung-Geun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.6
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    • pp.673-678
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    • 2003
  • In this paper, we proposes a method for face recognition using HMM(hidden Markov model) and wavelet coefficients First, input images are compressed by using the multi-resolution analysis based on the discrete wavelet transform. And then, the wavelet coefficients obtained from each subband are used as feature vectors to construct the HMMs. In the recognition stage, we obtained higher recognition rate by summing of each recognition rate of wavelet subband. The usefulness of the proposed method was shown by comparing with conventional VQ and DCT-HMM ones. The experimental results show that the proposed method is more satisfactory than previous ones.

Image Compression Technique Using Discrete Wavelet Transform and Fractal Theory (이산 웨이블렛 변환과 프렉탈 이론을 이용한 영상부호화 기법)

  • 김용호;정종근;편석범;이윤배
    • Journal of the Institute of Electronics Engineers of Korea TE
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    • v.39 no.4
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    • pp.423-430
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    • 2002
  • When JPEG, a standard of stopped image compression, is high compressed, the image is severely blocked. Since JPEG performs compression after taking DCT(Discrete Cosine Transform). It has a defect that the quality of image becomes low with aliasing in the case of high compression. Though transformation cipher method can have high compression rate, flame nay happen to quality of image by transformation and reverse transformation. In this paper, we use wavelet transform and fractal theory in order to solve these problems. After we apply these two methods to stopped image, we can get some good results, improvement of speed and compression rate, and elimination of blocking appearance. Besides, we show quality of restoration image is better than established one.

Quantitative Nondestructive Evaluation in Composite Beam Using Piezoelectric Transducers (압전 변환기를 이용한 복합재료 보의 비파괴 평가)

  • Lee, Sang-Hyoup;Choi, Young-Geun;Kim, Sang-Tae
    • Composites Research
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    • v.20 no.3
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    • pp.31-36
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    • 2007
  • A quantitative prediction method for initial crack length in a carbon/epoxy (CF/EP) composite beam using active piezoelectric transducers was established in this study. Wavelet Transform (WT)-based signal processing and identification technique in time-frequency domain was developed to facilitate the determination of damage presence and severity. Dynamic response of a CF/EP composites beam containing a continuously expanding crack, coupled with a pair of active piezoelectric disks, was examined under a narrow band excitation, and then applied with the proposed signal processing technique.

Audio Signal Coding Using Wavelet Transform (웨이블렛 변환을 이용한 오디오 코딩)

  • Bae, Seok-Mo;Kim, Do-Hyoung;Chung, Jae-Ho
    • The Journal of the Acoustical Society of Korea
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    • v.16 no.4
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    • pp.64-70
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    • 1997
  • This paper is aimed to propose a new wavelet audio signal coding scheme which reduces the complexity of well-known MPEG(Moving Picture Expert Group)-Audio. The filters of MPEG0audio apply subband technique on the 16-bits PCM audio to aquire bitstream of subband sample using dynamic bit allocation. If we use the wavelet coefficients instead of subband samples and 6 bands which is less than 32 bands of MPEG-audio, the complexity can be reduced. A new audio signal compression algorithm in this paper is based on wavelet transform and the proposed algorithm is compared with MPEG-audio. At the bitrate of 256kbps, the proposed algorithm maintains the CD(Compact-disc) quality. We were able to reduce the about 40% of complexity at encoder and about 70% at decoder.

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Wavelet-Based Fuzzy Modeling Using a DNA Coding Method (DNA 코딩 기법을 이용한 웨이브렛 기반 퍼지 모델링)

  • Joo, Young-Hoon;Lee, Yeun-Woo;Yu, Jin-Young
    • Journal of the Korean Institute of Intelligent Systems
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    • v.13 no.6
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    • pp.737-742
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    • 2003
  • In this paper, we propose a new wavelet-based fuzzy modeling using a DNA coding method. Generally, it is well known that the DNA coding method is more diverse in the knowledge expression and better in the optimization performance than the genetic algorithm (GA) because it can encode more plentiful genetic information based on the biological DNA. The proposed method makes a fuzzy model by using the wavelet transform, in which coefficients are identified by the DNA coding method. Thus we can effectively get the fuzzy model of nonlinear system by using the advantages of both wavelet transform and DNA coding method. In order to demonstrate the superiority of the proposed method, it is compared with the GA.

High Speed Wavelet Algorithm for Computation Reduction of Adaptive Signal Processing (적응신호처리의 계산량감소에 적합한 고속웨이블렛 알고리즘에 관한연구)

  • 오신범;이채욱
    • Journal of Korea Society of Industrial Information Systems
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    • v.7 no.4
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    • pp.17-21
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    • 2002
  • Least mean square(LMS) algorithm one of the most popular algorithm in adaptive signal processing because of the simplicity and the small computation. But the convergence speed of time domain adaptive algorithm is slow when the spread width of eigen values is wide. Moreover we have to choose the step size well for convergency. in this paper, ie use adaptive algorithm of wavelet transform. And we propose a new wavelet based adaptive algorithm of wavelet transform. And we propose a high speed wavelet based adaptive algorithm with variable step size, which is linear to absolute value of error signal. We applied this algorithm to adaptive noise canceler. Simulation results are presented to compare the performance of the proposed algorithm with the usual algorithms.

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