• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2003년도 하계학술대회 논문집
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• pp.268-271
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• 2003

There are several methods for the design of 2D filter. Notable among them is McClellan transform method. This transform allows us to obtain a high order 2D FIR filter through mapping the 1D frequency points of a 1D prototype FIR filter onto 2D frequency contours. We design 2D filter using this transform. Then we notice for mapping deviation of the 2D filter. In this paper, Quadratic programming (QP) method allows us to obtain coefficients of McClellan transform. Then we compare deviation of QP method with least-squares(LS) method. Elliptic filter is used for comparison. The optimal cutoff frequencies of a 1D filter are obtained directly from the QP method. Also several problem of LS method are solved.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1387-1390
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• 1997

In this paper we propose a novel way to restore degraded image using wavelet transform & filterbank. First, we devide a degraded image into 4-suband images using UDWT(Undecimated Wavelet Transform), and then use a proper CLS (Constrained Least Square) filter in each subband. Using a proper CLS filter ineach subband, we can save high grequency components of original image. We reconstruct a restored image from the downsampled subband images using wavelet tansform. Even though there is a trade-off between ISNR and calculation loads, we reduce the calculation loads by using wavelet transform in reconstruction with a negligible degradatiion in ISNR.

• 디지털산업정보학회논문지
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• 제11권1호
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• pp.171-182
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• 2015

The general wavelet transform has profitable property in non-stationary signal analysis specially. The tunable Q-factor wavelet transform is a fully-discrete wavelet transform for which the Q-factor Q and the asymptotic redundancy r, of the transform are easily and independently specified. In particular, the specified parameters Q and r can be real-valued. Therefore, by tuning Q, the oscillatory behavior of the wavelet can be chosen to match the oscillatory behavior of the signal of interest, so as to enhance the sparsity of a sparse signal representation. The TQWT is well suited to fast algorithms for sparsity-based inverse problems because it is a Parseval frame, easily invertible, and can be efficiently implemented. The transform is based on a real valued scaling factor and is implemented using a perfect reconstruction over-sampled filter bank with real-valued sampling factors. The transform is parameterized by its Q-factor and its over-sampling rate, with modest over-sampling rates being sufficient for the analysis/synthesis functions to be well localized. This paper describes filter design of 2D discrete-time wavelet transform for which the Q-factor is easily specified. With the advantage of this transform, perfect reconstruction filter design and implementation for performance improvement are focused in this paper. Hence, the 2D transform can be tuned according to the oscillatory behavior of the image signal to which it is applied. Therefore, application for performance improvement in multimedia communication field was evaluated.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.1379-1382
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• 1997

We introduce a fast implementation of the adaptive transversal filter which uses least-mean-square(LMS) algorithm. The fast Hadamard transform(FHT) is used for the implementation of the filter. By using the proposed filter we can get the significant time reduction in computatioin over the conventional time domain LMS filter at the cost of a little performance. By computer simulation, we show the comparison of the propsed Hadamard-domain filter and the time domain filter in the view of multiplication time, mean-square error and robustness for noise.

• 반도체디스플레이기술학회지
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• 제6권3호
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• pp.55-59
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• 2007

Wavelet Transform is amenable to efficient algorithms. So wavelet transform was adopted many signal processing and communication applications. For example, the wavelet transform was adopted as the transform for JPEG2000. However, Wavelet has weakness about smoothness along the contours and limited directional information. Hence, recently, some new transforms have been introduced to take advantage of this property. So we use to other transform, called contourlet transform in compression. In this paper, we propose a new method for image compression based on the contourlet transform, which has been recently introduced. Contourlet transform has a good result about images with smooth contours. Moreover, Contourlet is feasible multiresolution and multidirection expansion using non-separable filter bank. This treatise shows a good image representation after compressing using contourlet transform.

• 자원환경지질
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• 제20권2호
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• pp.119-123
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• 1987

0차의 Hankel 변환은 Abel 변환과 Fourier 변환의 결합으로 나타낼 수 있다. 이 Abel-Fourier법은 샘플링 간격이 일정하지 않는 중합필터를 사용한 신속한 Abel 변환과 고속 Fourier 변환으로 작성될 때, 종래의 디지탈 선형필터법보다 계산시간면에서 유리하다. 그러나, Abel-Fourier법은 일반적으로 잘 설계된 디지탈 필터보다 정확하지는 않다. 전기탐사 문제에 이들 방법을 적용할 때, 디지탈 필터법이 Abel-Fourier 법보다 더 융통성이 많은 것으로 생각된다.

• 융합신호처리학회논문지
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• 제9권4호
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• pp.295-303
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• 2008

변환영역 적응필터는 시간영역 적응필터보다 일반직으로 수렴속도가 빠르지만 필터의 차수가 증가함에 따라 계산량이 크게 증가한다. 이러한 문제점은 변환영역 적응필터를 서브밴드 분해구조로 변경함으로써 해결할 수 있다. 이 논문에서는 일반화된 서브밴드 분해 FIR 적응 필터의 수렴속도 향상을 위해 웨이블릿 변환영역에서 다이아딕 희소인자 서브필터를 가지는 일반화된 서브밴드 분해 FTR 적응 필터의 구조를 설계하였다. 그리고 이 적응필터에서 변환영역의 일반화된 등가입력을 유도하고 이 입력을 이용하여 LMS 일고리듬에 대한 수렴특성을 해석 및 평가하였다. 이 서브밴드 FIR 적응필터를 이용하여 역 모델링 시스템과 주기성 잡음제거기를 구성하고 LMS 알고리듬 대한 이 시스템들의 수련속도를 이산푸리에 변환을 이용한 서브밴드 적응필터의 것과 컴퓨터 모의실험으로 비교하였다.

• 융합신호처리학회논문지
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• 제9권4호
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• pp.253-260
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• 2008

영상향상 방법 중의 하나인 잡음제거는 공간영역과 변환영역 필터링에 대해서 많은 연구가 되어 왔다. 최근에는 에너지 집중도가 탁월하고 다분해능 성질을 갖는 웨이브릿 변환이 많이 사용되고 있다. 그러나 최종 사용자가 인간인 경우에는 인간시각체계에 기반한 변환을 사용하는 것이 시각적으로 유용하므로, 본 논문에서는 인간시각필터로 고려되는 Gabor 코사인과 사인 함수를 이용한 변환을 영상 잡음제거 분야에 적용하였다. 제안한 방법은 웨이브릿 변환과 다른 종류의 인간시각필터인 Gaussian 미분 변환에 대해서 피크신호대잡음비로 잡음제거 성능을 비교하였다. 여러 가지 잡음의 3가지 레벨에 대해서 실제 영상의 실험으로부터 제안한 변환이 BWT와 DGT보다 PSNR이 각각 0.41, 0.14dB 더 좋은 결과를 얻었다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
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• pp.505-508
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• 2005

Wavelet scheme can be applied to the various remote sensing problems: conventional multi-resolution image analysis, compression of large image sets, fusion of heterogeneous sensor image and segmentation of features. In this study, we attempted wavelet-based filtering and its analysis. Traditionally, statistical methods and adaptive filter are used to manipulate noises in the image processing procedure. While we tried to filter random noise from optical image and radar image using Discrete Wavelet Transform (DW1) and Stationary Wavelet Transform (SW1) and compared with existing methods such as median filter and adaptive filter. In result, SWT preserved boundaries and reduced noises most effectively. If appropriate thresholds are used, wavelet filtering will be applied to detect road boundaries, buildings, cars and other complex features from high-resolution imagery in an urban environment as well as noise filtering

• 전자공학회논문지D
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• 제34D권11호
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• pp.64-69
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• 1997

We have shown that the Hough transform filter can be easily obtained by repeatedly recording one line segment pattern holographically by use of rotational multiplexing. With this filter, one can get resutls of the hough transform in the time of light propagation. To demonstrate our method experimentally, the hough transform filter for 18 different rottion angles was recorded, and experimental transform results were compared with simulated ones for a few input patterns. By introducing a compensation process for the non-uniformity of both the input plane wav eand the diffraction efficiency of each hologram. It is possible to get more precise transform results.