• Journal of KIISE:Databases
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• v.33 no.7
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• pp.693-707
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• 2006

To improve performance using a multidimensional index in similar sequence matching, we transform a high-dimensional sequence to a low-dimensional sequence, and then construct a low-dimensional MBR that contains multiple transformed sequences. In this paper we propose a formal method that transforms a high-dimensional MBR itself to a low-dimensional MBR, and show that this method significantly reduces the number of lower-dimensional transformations. To achieve this goal, we first formally define the new notion of MBR-safe. We say that a transform is MBR-safe if a low-dimensional MBR to which a high-dimensional MBR is transformed by the transform contains every individual low-dimensional sequence to which a high-dimensional sequence is transformed. We then propose two MBR-safe transforms based on DFT and DCT, the most representative lower-dimensional transformations. For this, we prove the traditional DFT and DCT are not MBR-safe, and define new transforms, called mbrDFT and mbrDCT, by extending DFT and DCT, respectively. We also formally prove these mbrDFT and mbrDCT are MBR-safe. Moreover, we show that mbrDFT(or mbrDCT) is optimal among the DFT-based(or DCT-based) MBR-safe transforms that directly convert a high-dimensional MBR itself into a low-dimensional MBR. Analytical and experimental results show that the proposed mbrDFT and mbrDCT reduce the number of lower-dimensional transformations drastically, and improve performance significantly compared with the $na\"{\i}ve$ transforms. These results indicate that our MBR- safe transforms provides a useful framework for a variety of applications that require the lower-dimensional transformation of high-dimensional MBRs.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.4C
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• pp.440-446
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• 2007

This paper addresses a new representation of DFT matrix via the Jacket transform based on the element inverse processing. We simply represent the inverse of the DFT matrix following on the factorization way of the Jacket transform, and the results show that the inverse of DFT matrix is only simply related to its sparse matrix and the permutations. The decomposed DFT matrix via Jacket matrix has a strong geometric structure that exhibits a block modulating property. This means that the DFT matrix decomposed via the Jacket matrix can be interpreted as a block modulating process.

• Journal of Korea Society of Industrial Information Systems
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• v.10 no.2
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• pp.102-108
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• 2005

CIELAB coordinate is represented by one lightness component and two chromaticity components and similar to human visual system. Visual devices such as computer monitor display images using RGB coordinate. We propose a technique for inserting the watermark of visually recognizable mark into the middle frequency domain of image. RGB coordinate image is transformed into CIELAB coordinate, which include the characteristics of Human vision and then a* component is transformed into DFT(Discrete Fourier transform) transform.

• Journal of the Institute of Convergence Signal Processing
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• v.8 no.2
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• pp.106-112
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• 2007

This paper proposes a hybrid architecture algorithm for fast computation of DCT and DFT via recursive factorization. Recursive factorization of DCT-II and DFT transform matrix leads to a similar architectural structure so that common architectural base may be used by simply adding a switching device. Linking between two transforms was derived based on matrix recursion formula. Hybrid acrchitectural design for DCT and DFT matrix decomposition were derived using the generation matrix and the trigonometric identities and relations. Data flow diagram for high-speed architecture of Cooley-Tukey type was drawn to accommodate DCT/DFT hybrid architecture. From this data flow diagram computational complexity is comparable to that of the fast DCT algorithms for moderate size of N. Further investigation is needed for multi-mode operation use of FFT architecture in other orthogonal transform computation.

• 전기의세계
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• v.32 no.6
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• pp.317-324
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• 1983

신호처리방법의 하나인 transform coding에 있어서, unitary transform의 기본특성을 정리했고 FT(DFT)로부터 CFT(DCFT)를 유도했다. MP특성에 가까운 화상신호에 대한 1차원 변환에 대한 각종 transform을 비교하였다. 이것으로 DCT가 이들중 가장 KLT에 가깝다는 것과 DCFT가 DFT보다는 약간 좋은 특성을 갖는다는 것을 알 수 있다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.5
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• pp.1078-1084
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• 2010

This paper presents a speech enhancement system which restores the amplitude components and phase components by discrete Fourier transform (DFT), using neural network training by back-propagation algorithm. First, a neural network is trained using DFT amplitude components and phase components of noisy speech signal, then the proposed system enhances speech signals that are degraded by white noise using a neural network. Experimental results demonstrate that speech signals degraded by white noise are enhanced by the proposed system using the neural network, whose inputs are DFT amplitude components and phase components. Based on measuring spectral distortion measurement, experiments confirm that the proposed system is effective for white noise.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.27 no.1A
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• pp.51-57
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• 2002

In this paper, a simple interpolation technique in a frequency domain is proposed for the discrete Fourier transform(DFT) algorithm. Frequency and phase resolution capabilities of the DFT algorithm can be significantly improved by the proposed interpolation technique without increase of a DFT size(the number of points for the DFT). The new technique uses a diving point in amplitude and phase spectrums. As an application, the technique can be used for joint estimation of fine frequency and phase offsets in burst mode digital transmission. Simulation results show that the joint estimator using the technique is robust to estimation errors.

• Journal of The Korean Association of Information Education
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• v.15 no.3
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• pp.517-524
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• 2011

This paper presents a fast blind deconvolution method that produces a deblurring result from a single image in only a few seconds. The high speed of our method is enabled by considering the Discrete Fourier Transform (DFT), and its relation to filtering and convolution, and fast computation of Moore-Penrose inverse matrix. How can we predict the behavior of an arbitrary filter, or even more to the point design a filter to achieve certain specifications. The idea is to study the frequency response of the filter. This concept leads to an useful convolution formula. A Matlab implementation of our method usually takes less than one minute to deblur an image of moderate size, while the deblurring quality is comparable.

• Proceedings of the IEEK Conference
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• 2001.09a
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• pp.107-110
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• 2001

In this paper, we propose a multiplication-free DFT kernel computation technique, whose input sequences are approximated into a ring of Algebraic Integers. This paper also gives computational examples for DFT and IDFT. And we proposes an architecture of the DFT using barrel shifts and adds. When the radix is greater than 4, the proposed method has a high Precision property without scaling errors due to twiddle factor multiplication. A possibility of higher radix system assumes that higher performance can be achievable for reducing the DFT stages in FFT.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.37 no.5
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• pp.9-20
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• 2000

In this paper we compare two frequency domain digital watermarking methods for digital Images, namely DCT(Discrete Cosine Transform) based and DFT(Discrete Fourier Transform) based methods. Unlike DCT coefficients, which always have real values, DFT coefficients normally have complex values Therefore, the DFT coefficients have amplitude and phase components Among them, the phase components are known to carry more Important information for the Images. So, we insert the watermark to the phase of the DFT coefficients only This DFT watermarking method is compared with the conventional DCT based watermarking method for the object-based watermarking problem. Experimental results show that the DFT-phase based method IS more robust to general Image processing attacks including resize, lossy compression(JPEG), blurring and median filtering. On the other hand, the DCT based method is more robust to the malicious attack which inserts different watermarks.