• Journal of the Institute of Convergence Signal Processing
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• v.11 no.1
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• pp.41-46
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• 2010

In this paper, the DoA(Direction of Arrival) estimator using unitary MUSIC algorithm is studied. The complex-valued correlation matrix of MUSIC algorithm is transformed to the real-valued one using unitary transform for easy implementation. The eigenvalue and eigenvector are obtained by the combined Jacobi-CORDIC algorithm. CORDIC algorithm can be implemented by only ADD and SHIFT operations and MUSIC spectrum computed by 256 point DFT algorithm. Results of unitary MUSIC algorithm designed by System Generator for FPGA implementation is entirely consistent with Matlab results. Its performance is evaluated through hardware co-simulation and resource estimation.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.102-107
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• 2007

Since the Matrix Pencil (MP) method can be performed to estimate multiple DOAs by using only single snapshot, this method is suitable for short data length or when the environment is dynamic. As the number of array increases, the computational load increases due to complex number computation. This paper presents an approach based on a unitary matrix pencil (MP) algorithm to reduce the computational load. Unitary transformation for the MP method has been suggested and formulated successfully. The computer simulation shows that the error rate of proposed method agree with that of MP for different SNR values.

• 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 Chungcheong Mathematical Society
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• v.8 no.1
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• pp.137-145
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• 1995

In the white noise analysis the one-parameter groups play the powerful role. In this report, we will see a subgroup of infinite dimensional unitary group $U_{\infty}$ including guage transform and structure of this subgroup under the view point of Lie algebra.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.3
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• pp.263-269
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• 2003

This paper focuses on lossy medical image compression methods for medical images that operate on three-dimensional(3D) irreversible integer wavelet transform. We offer an application of the Set Partitioning in Hierarchical Trees(SPIHT) algorithm〔l-3〕to medical images, using a 3-D wavelet decomposition and a 3-D spatial dependence tree. The wavelet decomposition is accomplished with integer wavelet filters implemented with the lifting method, where careful scaling and truncations keep the integer precision small and the transform unitary. As the compression rate increases, the boundaries between adjacent coding units become increasingly visible. Unlike video, the volume image is examined under static condition, and must not exhibit such boundary artifacts. In order to eliminate them, we utilize overlapping at axial boundaries between adjacent coding units. We have tested our encoder on medical images using different integer filters. Results show that our algorithm with certain filters performs as well. The improvement is visibly manifested as fewer ringing artifacts and noticeably better reconstruction of low contrast.

• Proceedings of the IEEK Conference
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• 2002.07b
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• pp.1015-1018
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• 2002

We show how any discrete wavelet transform or two band subband filtering with finite filters can be decomposed onto a finite sequence of simple filtering steps, which we call lifting steps but that are also known as ladder structures, We present a self-contained derivations, building the decomposition from the basic principles such as the Euclidean algorithm, with a focus on a applying it to wavelet filtering. This factorization provides an alternative for the lattice factorization, with the advantage that it can also be used in the bi-orthogonal, i.e, non-unitary case. Lifting leads to a speed-up when compared to the standard implementation. We show that this lifting scheme can be applied in image compression efficiently

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2395-2398
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• 2003

This paper focuses on lossless medical image compression methods for medical images that operate on two-dimensional(2D) reversible integer wavelet transform. We offer an application of the Set Partitioning in Hierarchical Trees(SPIHT) algorithm [1][3][9] to medical images, using a 2D wavelet decomposition and a 2D spatial dependence tree. The wavelet decomposition is accomplished with integer wavelet filters implemented with the lifting method, where careful scaling and truncations keep the integer precision small and the transform unitary. We have tested our encoder on medical images using different integer filters. Results show that our algorithm with certain filters performs as well and sometimes better in lossless coding than previous coding systems using 2D integer wavelet transforms on medical images.

• Proceedings of the Korean Society Of Semiconductor Equipment Technology
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• 2004.05a
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• pp.217-222
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• 2004

This paper focuses on lossy medical image compression methods for medical images that operate on two-dimensional(2D) integer wavelet transform. We offer an application of the Set Partitioning in Hierarchical Trees(SPIHT) algorithm to medical images, using a 2D wavelet decomposition and a 2D spatial dependence tree. The wavelet decomposition is accomplished with integer wavelet filters implemented with the lifting method, where careful scaling and truncations keep the integer precision small and the transform unitary. We have tested our encoder on medical images using different integer filters. Results show that our algorithm with certain filters performs as well and is sometimes better lossy coding using 2D integer wavelet transforms on medical images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.22 no.12
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• pp.2706-2713
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• 1997

The fast implementation algorithm of M-band discrete wavelet transform is propsed using the factorization of lossless matrix when the length of discrete orthogonal wavelet bases equals to 2M. In computational complexity when direct filtering method is employed, the number of multiplicationand addition is (2M$^{2}$) and (2M$^{2}$ -M), respectively. But by proposed algorithm, it can be reduced to (M$^{2}$+M) and (M$^{2}$+2M-1), respectively. and it is possible to reduce the compuatational complexity further when unitary matrix employed to design the discrete or thogonal wavelet basis has the fast algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.4
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• pp.820-828
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• 2017

Service of digital hologram that has been recognized as a visual system for next generation requires various signal processing technologies. A transform is the most frequently used tool among signal processing techniques for 2-dimensional(D) and 3-D natural picture. A digital hologram has totally different property with a natural picture, so it is rarely efficient to apply transform tools used in 2-D image processing to a digital hologram. To overcome this a Fresnelet transform for a digital hologram has been proposed. We derive a Fresnelet transform by using the Daubechie's filter after applying an unitary Fresnel transform to a wavelet basis function. We also implement the transform as types of device and kernel code to improve operational performance. In consideration of the average time that is required for a pixel we can have observed the performance is improved up to 242 and 30 times for using the (9,7) and (5,3) filters in case of using device code.