• 제목/요약/키워드: transform

검색결과 10,467건 처리시간 0.032초

ANALYTIC FOURIER-FEYNMAN TRANSFORM AND CONVOLUTION OF FUNCTIONALS IN A GENERALIZED FRESNEL CLASS

  • Kim, Byoung Soo;Song, Teuk Seob;Yoo, Il
    • 충청수학회지
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    • 제22권3호
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    • pp.481-495
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    • 2009
  • Huffman, Park and Skoug introduced various results for the $L_{p}$ analytic Fourier-Feynman transform and the convolution for functionals on classical Wiener space which belong to some Banach algebra $\mathcal{S}$ introduced by Cameron and Storvick. Also Chang, Kim and Yoo extended the above results to an abstract Wiener space for functionals in the Fresnel class $\mathcal{F}(B)$ which corresponds to $\mathcal{S}$. Moreover they introduced the $L_{p}$ analytic Fourier-Feynman transform for functionals on a product abstract Wiener space and then established the above results for functionals in the generalized Fresnel class $\mathcal{F}_{A1,A2}$ containing $\mathcal{F}(B)$. In this paper, we investigate more generalized relationships, between the Fourier-Feynman transform and the convolution product for functionals in $\mathcal{F}_{A1,A2}$, than the above results.

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Hough 변환을 이용한 암묵신호분리방법 (Blind Signal Separation Method using Hough Transform)

  • 이행우
    • 디지털산업정보학회논문지
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    • 제10권3호
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    • pp.143-149
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    • 2014
  • This paper is on the blind signal separation(BSS) method by the geometric method. To separate the signal sources, we use Hough transform and BSS. Hough transform is a geometric method which let us know the local informations of the signal. We find the orientations of signals by Hough transform and know the number of signal sources. When the number of sensors is more than the number of sources. the BSS algorithm can separate the mixtures well in the time domain. This algorithm has a good performance in converging fast. We had checked up the quality of the algorithm after separating the mixed signals. The results of simulations show that this BSS method has the abnormal waveforms due to unconverging coefficients in the beginning, and stably has the separated waveforms which almost equal to the sources in the most period.

웨이브렛 변환 영역에서 쿼드트리 기반 영상압축 (Quadtree Based Image Compression in Wavelet Transform Domain)

  • 소이빈;조창호;이상효;이상철;박종우
    • 대한전자공학회:학술대회논문집
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    • 대한전자공학회 2003년도 하계종합학술대회 논문집 Ⅳ
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    • pp.2303-2306
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    • 2003
  • The Wavelet Transform providing both of the frequency and time 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 multiresolution theory are going on. This paper proposes a Quadtree decompositon method of image compression applied to the images decomposed by wavelet transform by using the correlations between pixels .Since the coefficients obtained by the wavelet transform have high correlations between scales, the Quadtree method can reduce the data quantity effectively The experimental image with 256${\times}$256 size was used to compare the Performances of the existing and the proposed compression methods.

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Residual DPCM in HEVC Transform Skip Mode for Screen Content Coding

  • Han, Chan-Hee;Lee, Si-Woong;Choi, Haechul
    • IEIE Transactions on Smart Processing and Computing
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    • 제5권5호
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    • pp.323-326
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    • 2016
  • High Efficiency Video Coding (HEVC) adopts intra transform skip mode, in which a residual block is directly quantized in the pixel domain without transforming the block into the frequency domain. Intra transform skip mode provides a significant coding gain for screen content. However, when intra-prediction errors are not transformed, the errors are often correlated along the intra-prediction direction. This paper introduces a residual differential pulse code modulation (DPCM) method for the intra-predicted and transform-skipped blocks to remove redundancy. The proposed method performs pixel-by-pixel residual prediction along the intra-prediction direction to reduce the dynamic range of intra-prediction errors. Experimental results show that the transform skip mode's Bjøntegaard delta rate (BD-rate) is improved by 12.8% for vertically intra-predicted blocks. Overall, the proposed method shows an average 1.2% reduction in BD-rate, relative to HEVC, with negligible computational complexity.

Noise Suppression in NMR Spectrum by Using Wavelet Transform Analysis

  • Kim, Daesung;Youngdo Won;Hoshik Won
    • 한국자기공명학회논문지
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    • 제4권2호
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    • pp.103-115
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    • 2000
  • Wavelet transforms are introduced as a new tool to distinguish real peaks from the noise contaminated NMR data in this paper. New algorithms of two wavelet transforms including Daubechies wavelet transform as a discrete and orthogonal wavelet transform (DWT) and Morlet wavelet transform as a continuous and nonorthogonal wavelet transform(CWT) were developed fer noise elimination. DWT and CWT method were successfully applied to the noise reduction in spectrum. The inevitable distortion of NMR spectral baseline and the imperfection in noise elimination were observed in DWT method while CWT method gives a better baseline ahape and a well noise suppressed spectrum.

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AWGN 환경에서 웨이브렛을 이용한 잡음 제거 방법에 관한 연구 (A Study on Denoising Methods using Wavelet in AWGN environment)

  • 배상범;김남호
    • 한국정보통신학회논문지
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    • 제5권5호
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    • pp.853-860
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    • 2001
  • 본 논문에서는 웨이브렛을 이용한 두 가지 새로운 잡음 제거 방법으로, 공간적 상관관계를 이용한 NSSNF(new spatially selective noise filtration)과 threshold에 기초한 UDWT(undecimated discrete wavelet transform)을 제시한다. NSSNF에서는 기존의 SSNF에 새로운 파라메타를 추가하여, 융통성 있는 SNR 이득 특성을 얻도록 하였으며, UDWT에서는 hard-threshold를 적용하여, 기존의 soft-threshold를 적용한 OWT(orthogonal wavelet transform)보다 우수한 잡음 제거 효과를 얻도록 하였다. 이러한 테스트 환경으로는 AWGN을 선택하였으며, 개선 효과의 판단 기준으로 SNR을 사용하여, 기존의 잡음 제거 방법과 비교 분석하였다.

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PROPOSAL OF AMPLITUDE ONLY LOGARITHMIC RADON DESCRIPTER -A PERFORMANCE COMPARISON OF MATCHING SCORE-

  • Hasegawa, Makoto
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2009년도 IWAIT
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    • pp.450-455
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    • 2009
  • Amplitude-only logarithmic Radon transform (ALR transform) for pattern matching is proposed. This method provides robustness for object translation, scaling, and rotation. An ALR image is invariant even if objects are translated in a picture. For the object scaling and rotation, the ALR image is merely translated. The objects are identified using a phase-only matched filter to the ALR image. The ratio of size, the difference of rotation angle, and the position between the two objects are detected. Our pattern matching procedure is described, herein, and its simulation is executed. We compare matching scores with the Fourier-Mellin transform, and the general phase-only matched filter.

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Improvement of reconstructed image from computer generated psuedo holograms using iterative method

  • Sakanaka, Kouta;Tanaka, Kenichi
    • 한국방송∙미디어공학회:학술대회논문집
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    • 한국방송공학회 2009년도 IWAIT
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    • pp.578-582
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    • 2009
  • Computer-Generated Hologram (CGH) is generally made by Fourier Transform. CGH is made by an optical reconstruction. Computer-Generated Pseudo Hologram (CGPH) is made up Complex Hadamard Transform instead of CGH which is made by the Fourier Transform. CGPH differs from CGH in point of view the possibility of optical reconstruction. There is an advantage that it cannot be optical reconstruction, in other word, physical leakage of the confidential information is impossible. In this paper, a binary image was converted in Complex Hadamard Transform, and CGPH was made. Improvement of the reconstructed image from CGPH is done by error diffusion method and iterative method. The result that the reconstructed image is improved is shown.

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Wavelet Transform을 이용한 Key-frame 검색 (Retrieval of Key-frames using Wavelet Transform)

  • 정세윤;김규헌;전병태;이재연;배영래
    • 한국정보과학회:학술대회논문집
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    • 한국정보과학회 1998년도 가을 학술발표논문집 Vol.25 No.2 (2)
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    • pp.509-511
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    • 1998
  • 본 논문에서는 동영상 데이터베이스에서 Key-frame을 검색하는 방법을 제안한다. 본 논문에서는 Key-frame을 검색하기위해 컬러 피쳐를 공간영역에서 추출하지 않고 wavelet transform 영역에서 컬러 피쳐를 추출하는 방법을 제안한다. wavelet transform 의 저주파 밴드는 영상전체의 특징을 잘 나타내고 고주파 밴드는 texture 와 국부적인 컬러 특성을 잘 나타낸다. 색인과정 알고리즘은 영상의 크기를 정규화하고 RGB 컬러공간에서 HSV 컬러 공간으로 변환을 하여, H, S, V 각 채널에 대해 Daubechies' wavelet transform을 수행한 후 변환 영역에서 피쳐를 추출하게 된다. 색인을 위한 피쳐로 wavelet 계수와 lowest 밴드의 평균과 표준편차를 추출하였다. 효율적인 검색을 위해 검색은 2단계로 수행된다. 먼저 평균과 표준편차만을 이용한 1차 검색을 통해 2차 검색의 후보 영상들을 추출하고 2차 검색에서는 1차 검색 통과 영상들에 대해서만 wavelet 계수들을 비교하여 최종 검색 결과를 얻게 된다. 검색결과 기존의 컬러 피쳐를 이용한 방법보다 우수한 검색결과를 얻을 수 있었다.

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이산 웨이브렛 변환을 이용한 2차원 물체 인식에 관한 연구 (Analysis of 2-Dimensional Object Recognition Using discrete Wavelet Transform)

  • 박광호;김창구;기창두
    • 한국정밀공학회지
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    • 제16권10호
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    • pp.194-202
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    • 1999
  • A method for pattern recognition based on wavelet transform is proposed in this paper. The boundary of the object to be recognized includes shape information for object of machine parts. The contour is first represented using a one-dimensional signal and normalized about translation, rotation and scale, then is used to build the wavelet transform representation of the object. Wavelets allow us to decompose a function into multi-resolution hierarchy of localized frequency bands. The recognition of 2-dimensional object based on the wavelet is described to analyze the shape of analysis technique; the discrete wavelet transform(DWT). The feature vectors obtained using wavelet analysis is classified using a multi-layer neural network. The results show that, compared with the use of fourier descriptors, recognition using wavelet is more stable and efficient representation. And particularly the performance for objects corrupted with noise is better than that of other method.

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