• Title/Summary/Keyword: Transform Domain

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Adaptive Quantization for Transform Domain Wyner-Ziv Residual Coding of Video (변환 영역 Wyner-Ziv 잔차 신호 부호화를 위한 적응적 양자화)

  • Cho, Hyon-Myong;Shim, Hiuk-Jae;Jeon, Byeung-Woo
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.48 no.4
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    • pp.98-106
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    • 2011
  • Since prediction processes such as motion estimation motion compensation are not at the WZ video encoder but at its decoder, WZ video compression cannot have better performance than that of conventional video encoder. In order to implement the prediction process with low complexity at the encoder, WZ residual coding was proposed. Instead of original WZ frames, WZ residual coding encodes the residual signal between key frames and WZ frames. Although the proposed WZ residual coding has good performance in pixel domain, it does not have any improvements in transform domain compared to transform domain WZ coding. The WZ residual coding in transform domain is difficult to have better performance, because pre-defined quantization matrices in WZ coding are not compatible with WZ residual coding. In this paper, we propose a new quantization method modifying quantization matrix and quantization step size adaptively for transform domain WZ residual coding. Experimental result shows 22% gain in BDBR and 1.2dB gain in BDPSNR.

Multispectral Image Data Compression Using Classified Prediction and KLT in Wavelet Transform Domain (웨이블릿 영역에서 분류 예측과 KLT를 이용한 다분광 화상 데이터 압축)

  • 김태수;김승진;이석환;권기구;김영춘;이건일
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.29 no.4C
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    • pp.533-540
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    • 2004
  • This paper proposes a new multispectral image data compression algorithm that can efficiently reduce spatial and spectral redundancies by applying classified prediction, a Karhunen-Loeve transform (KLT), and the three-dimensional set partitioning in hierarchical trees (3-D SPIHT) algorithm in the wavelet transform (WT) domain. The classification is performed in the WT domain to exploit the interband classified dependency, while the resulting class information is used for the interband prediction. The residual image data on the prediction errors between the original image data and the predicted image data is decorrelated by a KLT. Finally, the 3-D SPIHT algorithm is used to encode the transformed coefficients listed in a descending order spatially and spectrally as a result of the WT and KLT. Simulation results showed that the reconstructed images after using the proposed algorithm exhibited a better quality and higher compression ratio than those using conventional algorithms.

Low delay window switching modified discrete cosine transform for speech and audio coder (음성 및 오디오 부호화기를 위한 저지연 윈도우 스위칭 modified discrete cosine transform)

  • Kim, Young-Joon;Lee, In-Sung
    • The Journal of the Acoustical Society of Korea
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    • v.37 no.2
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    • pp.110-117
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    • 2018
  • In this paper, we propose a low delay window switching MDCT (Modified Discrete Cosine Transform) method for speech/audio coder. The window switching algorithm is used to reduce the degradation of sound quality in non-stationary trasient duration and to reduce the algorithm delay by using the low delay TDAC (Time Domain Aliasing Cancellation). While the conventional window switching algorithms uses overlap-add with different lengths, the proposed method uses the fixed overlap add length. It results the reduction of algorithm delay by half and 1 bit reduction in frame indication information by using 2 window types. We apply the proposed algorithm to G.729.1 based on MDCT in order to evaluate the performance. The propose method shows the reduction of algorithm delay by half while speech quality of the proposed method maintains same as the conventional method.

The Fractal Image Compression Based on the Wavelet Transform Using the SAS Techniques (SAS 기법을 이용한 웨이브릿 변환 기반 프랙탈 영상 압축)

  • 정태일;강경원;문광석;권기룡;류권열
    • Journal of the Institute of Convergence Signal Processing
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    • v.2 no.1
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    • pp.19-27
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    • 2001
  • The conventional fractal image compression based on wavelet transform has the disadvantage that the encoding takes many time, since it finds the optimum domain for all the range blocks. In this paper, we propose the fractal image compression based on wavelet transform using the SAS(Self Affine System) techniques. It consists of the range and domain blocks in the wavelet transform, and the range blocks select the domain which is located the relatively same position. In the encoding process, the proposed methods introduce SAS techniques that the searching process of the domains blocks is not required. Therefore, it can perform a fast encoding by reducing the computational complexity. And, the image quality is improved using the different scale factors for each level and the sub-tree in the decoding. As a result, the image quality and the compression ratio are adjustable by the scale factors.

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Fault Diagnosis of Induction Motors by DFT and Wavelet (DFT와 웨이블렛을 이용한 유도전동기 고장진단)

  • Kwon, Mann-Jun;Lee, Dae-Jong;Park, Sung-Moo;Chun, Myung-Geun
    • Journal of the Korean Institute of Intelligent Systems
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    • v.17 no.6
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    • pp.819-825
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    • 2007
  • In this paper, we propose a fault diagnosis algorithm of induction motors by DFT and wavelet. We extract a feature vector using a fault pattern extraction method by DFT in frequency domain and wavelet transform in time-frequency domain. And then we deal with a fusion algorithm for the feature vectors extracted from DFT and wavelet to classify the faults of induction motors. Finally, we provide an experimental results that the proposed algorithm can be successfully applied to classify the several fault signals acquired from induction motors.

On the Linearization of Volterra Nonlinear Systems using DWT and a Predistorter (DWT 및 전치 왜곡기를 이용한 볼테라 시스템 선형화)

  • 강동준;김영근;남상원
    • Proceedings of the IEEK Conference
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    • 2000.09a
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    • pp.553-556
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    • 2000
  • This paper proposes an adaptive linearization method of Volterra nonlinear systems using DWT(Discrete Wavelet Transform)and an LMS-type predistorter. In particular, the proposed wavelet transform-domain lineatization method leads to diagonalization of the input vector auto-correlation matrix which yields improvement of the convergence rate of the corresponding transform-domain LMS algorithm. Furthermore, the adaptive Volterra predistorter followed by a corresponding weakly Volterra nonlinear system(here. a TWT amplifier model in a satellite communication system) is utilized to compensate for the distortion in the output. Also,12-PSK and 4-QAM are applied as the input to the nonlinear system to be tested. Some simulation results show that the proposed linearization approach has better performance than DCT-based or conventional normalized LMS algorithms do.

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A Study on the Watermarking Methods with Chi-Square Distribution (카이 자승 분포를 이용한 워터마킹기법의 연구)

  • 강환일;김갑일;한승수
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2001.12a
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    • pp.5-9
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    • 2001
  • In this paper, we propose the new audio watermarking method and can be used on line processing. Instead of the wavelet transform, we use the integer wavelet transform for the reduction of the computational load. The watermark associated with the chi-square distribution is inserted into the signal on the integer wavelet domain. When extracting the watermark, the spread spectrum methods are used with the coefficients associated with the covariance sequence. We show that the chi-square distribution is a good tool for the spread spectrum method on the wavelet domain. This watermarking technique may be used for the control of the electrical product which can be controlled with the hidden signals and can be moved according to the audible signals simultaneously.

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Efficient Transform-Domain Noise Reduction for H.264 Video Encoding (H.264 동영상 부호화를 위한 효과적인 주파수 영역 잡음 제거)

  • Song, Byung-Cheol
    • Journal of Broadcast Engineering
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    • v.14 no.4
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    • pp.501-508
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    • 2009
  • This paper proposes an efficient transform-domain noise reduction scheme in an H.264 video encoder, where the generalized Wiener filtering is performed in a quantization process by multiplying each transform block with its adaptive multiplication factor. In practice, the computational complexity of the proposed scheme is negligible by replacing the multiplication operation with a simple look-up table method. Also, experimental results show that the proposed scheme provides outstanding noise reduction performance in an H.264 video encoder.

Thermal Analysis of Automotive Disc Brake Using FFT-FEM (FFT-FEM을 이용한 자동차용 디스크 브레이크의 열 해석)

  • Choi, Ji-Hoon;Kim, Do-Hyung;Lee, In
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.25 no.8
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    • pp.1253-1260
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    • 2001
  • Transient thermal analysis of a three-dimensional axisymmetric automotive disk brake is presented in this paper. Temperature fields are obtained using a hybrid FFT-FEM scheme that combines Fourier transform techniques and finite element method. The use of a fast Fourier transform algorithm can avoid singularity problems and lead to inexpensive computing time. The transformed problem is solved with finite element scheme for each frequency domain. Inverse transforms are then performed for time domain solution. Numerical examples are presented for validation tests. Comparisons with analytical results show very good agreement. Also, a 3-D simulation, based upon an automotive brake disk model is performed.

Adaptive Watermark Detection Algorithm Using Perceptual Model and Statistical Decision Method Based on Multiwavelet Transform

  • Hwang Eui-Chang;Kim Dong Kyue;Moon Kwang-Seok;Kwon Ki-Ryong
    • Journal of Korea Multimedia Society
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    • v.8 no.6
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    • pp.783-789
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    • 2005
  • This paper is proposed a watermarking technique for copyright protection of multimedia contents. We proposed adaptive watermark detection algorithm using stochastic perceptual model and statistical decision method in DMWT(discrete multi wavelet transform) domain. The stochastic perceptual model calculates NVF(noise visibility function) based on statistical characteristic in the DMWT. Watermark detection algorithm used the likelihood ratio depend on Bayes' decision theory by reliable detection measure and Neyman-Pearson criterion. To reduce visual artifact of image, in this paper, adaptively decide the embedding number of watermark based on DMWT, and then the watermark embedding strength differently at edge and texture region and flat region embedded when watermark embedding minimize distortion of image. In experiment results, the proposed statistical decision method based on multiwavelet domain could decide watermark detection.

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