• 전자공학회논문지
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• 제51권9호
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• pp.30-40
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• 2014

본 논문에서는 Hadamard 변환이 Jacket 변환으로 일반화 될 수 있는 것처럼 Haar 변환을 Jacket-Haar 변환으로 일반화 한다. Jacket-Haar 변환의 원소는 0 과 ${\pm}2^k$ 이다. original Haar 변환과 비교해서 Jacket-Haar 변환의 베이시스(basis)는 신호처리에 보다 적합하다. 응용으로 $2{\times}2$ Hadamard 행렬을 기반으로 한 DCT-II(discrete cosine transform-II)와 $2{\times}2$ Haar 행렬을 기반으로 한 HWT(Haar Wavelete transform)를 제시하고 이들의 성능을 분석하며 Lenna 이미지의 시뮬레이션을 통해 성능을 평가하였다.

• 한국정보통신학회논문지
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• 제13권12호
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• pp.2731-2736
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• 2009

본 논문에서는 직교 기저행렬을 이용한 직교 주파수분할다중화 시스템의 새로운 구현방안이 수학적으로 개발된다. 직교기저행렬은 Haar 기저행렬을 기본으로 하고 있으나 직교 주파수분할다중화의 다중 부채널 신호를 변조하기에 적당한 형태를 갖추고 있다. 여기서는 새로운 기저행렬이 간단한 재귀알고리즘에 의하여 확장될 수 있음이 증명된다.그리고 송신기 조합행렬의 차수는 확장에 의하여 두배로 증가된다. 수신기에서 복조는 직교 기저행렬의 재귀에 의하여 생성되는 조합행렬의 역행렬에 의하여 수행된다. 따라서 제안된 직교 주파수분할다중화 시스템에서는 원 신호의 완벽한 재생이 가능함을 알 수 있다.

• 대한원격탐사학회지
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• 제24권1호
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• pp.57-64
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• 2008

In the previous study, the Haar wavelet was used as the sole basis function for the 3D discrete wavelet transform because the number of bands is too small to decompose a remotely sensed image in band direction with other basis functions. However, it is possible to use other basis functions for wavelet decomposition in horizontal and vertical directions because wavelet decomposition is independently performed in each direction. This study aims to classify a high spatial resolution image with the six types of basis function including the Haar function and to compare those results. The other wavelets are more helpful to classify high resolution imagery than the Haar wavelet. In overall accuracy, the Coif4 wavelet has the best result. The improvement of classification accuracy is different depending on the type of class and the type of wavelet. Using the basis functions with long length could be effective for improving accuracy in classification, especially for the classes of small area. This study is expected to be used as fundamental information for selecting optimal basis function according to the data properties in the 3D DWT based image classification.

• 한국통신학회:학술대회논문집
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• 한국통신학회 1984년도 춘계학술발표회논문집
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• pp.13-17
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• 1984

A hybrid version of the Hadamard and center Line Symmetric Haar Transform called H-CLSH is defined and developed. Efficient algorithms for fast computation of the H-CLSH and its inverse are developed. The H-CLSH is applied to digital signal and image processing and its utility and image processing and its utility and effectiveness are compared with Hadamard-Haar discrete transforms on the basis of some standard performance criteria.

• Structural Engineering and Mechanics
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• 제45권1호
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• pp.95-110
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• 2013

In the recent decade, practical of wavelet technique is being utilized in various domain of science. Particularly, engineers are interested to the wavelet solution method in the time series analysis. Fundamentally, seismic responses of structures against time history loading such as an earthquake, illustrates optimum capability of systems. In this paper, a procedure using particularly discrete Haar wavelet basis functions is introduced, to solve dynamic equation of motion. In the proposed approach, a straightforward formulation in a fluent manner is derived from the approximation of the displacements. For this purpose, Haar operational matrix is derived and applied in the dynamic analysis. It's free-scaled matrix converts differential equation of motion to the algebraic equations. It is shown that accuracy of dynamic responses relies on, access of load in the first step, before piecewise analysis added to the technique of equation solver in the last step for large scale of wavelet. To demonstrate the effectiveness of this scheme, improved formulations are extended to the linear and nonlinear structural dynamic analysis. The validity and effectiveness of the developed method is verified with three examples. The results were compared with those from the numerical methods such as Duhamel integration, Runge-Kutta and Wilson-${\theta}$ method.

• 대한원격탐사학회지
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• 제25권3호
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• pp.215-223
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• 2009

The noise removal as a preprocessing was tried with various kinds of wavelet pairs. Wavelet transform for 2D images generally uses the same wavelets as basis functions in horizontal and vertical directions. A method with different wavelets was tried for each direction separately, which gives more precise interpretation of the classification. Total 486 pairs of wavelets from nine basis functions were tried to remove image noises. The classification accuracies before and after the noise removal were compared. Although all kinds of wavelet pairs showed the increased accuracies in classification, there were best and worst wavelet pairs depending on the data sets. Wavelet pairs with low energy percentage of LL band showed the high classification accuracy. A pattern was found in the results that very similar vertical accuracy was distributed for each horizontal ones. Since Haar is the shortest length filter, Haar could be a predictor wavelet to find the good wavelet pairs.

• 대한원격탐사학회지
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• 제24권5호
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• pp.437-444
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• 2008

Land-use or land-cover classification of satellite images is one of the important tasks in remote sensing application and many researchers have tried to enhance classification accuracy. Previous studies have shown that the classification technique based on wavelet transform is more effective than traditional techniques based on original pixel values, especially in complicated imagery. Various basis functions such as Haar, daubechies, coiflets and symlets are mainly used in 20 image processing based on wavelet transform. Selecting adequate wavelet is very important because different results could be obtained according to the type of basis function in classification. However, it is not easy to choose the basis function which is effective to improve classification accuracy. In this study, we first computed the wavelet coefficients of satellite image using ten different basis functions, and then classified images. After evaluating classification results, we tried to ascertain which basis function is the most effective for image classification. We also tried to see if the optimum basis function is decided by energy parameter before classifying the image using all basis functions. The energy parameters of wavelet detail bands and overall accuracy are clearly correlated. The decision of optimum basis function using energy parameter in the wavelet based image classification is expected to be helpful for saving time and improving classification accuracy effectively.

• 한국정보통신학회논문지
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• 제20권4호
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• pp.826-832
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• 2016

본 논문에서는 고가의 디지털 설진 장비와 특별한 장치 없이 누구나 손쉽게 사용할 수 있는 디지털 설진 시스템의 첫 단계로 미각 영역별 균열 유무를 판별하는 시스템을 제안한다. 훈련 DB는 한방 병원에서 수집한 사진 261장을 바탕으로 Haar-like feature, Adaboost 학습을 하였다. 학습된 결과를 통하여 입력영상으로부터 혀 후보영역을 검출하고, 검출된 혀 후보영역으로부터 혀 영역만을 분리하기 위하여 261장의 훈련 DB의 HSV 컬러모델의 Hue 성분 평균 값을 산출하였다. 검출된 혀 윤곽으로부터 Connected Component Labeling을 통하여 혀 영역을 분리 하였다. 분리된 혀 영역의 상대적 너비와 높이를 이용하여 미각 영역별 로 분할하였다. 분할된 미각 영역별 영상은 Gray영상으로 변환하고, 각각의 영역별 평균 밝기를 산출하여 이진화하였다. 이진화 영상에 Connected Component Labeling을 통하여 균열 유무를 판별하였다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2008년도 International Symposium on Remote Sensing
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• pp.169-172
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• 2008

Land-use or land-cover classification of satellite images is one of the important tasks in remote sensing application and many researchers have been tried to enhance classification accuracy. Previous studies show that the classification technique based on wavelet transform is more effective than that of traditional techniques based on original pixel values, especially in complicated imagery. Various wavelets can be used in wavelet transform. Wavelets are used as basis functions in representing other functions, like sinusoidal function in Fourier analysis. In these days, some basis functions such as Haar, Daubechies, Coiflets and Symlets are mainly used in 2D image processing. Selecting adequate wavelet is very important because different results could be obtained according to the type of basis function in classification. However, it is not easy to choose the basis function which is effective to improve classification accuracy. In this study, we computed the wavelet coefficients of satellite image using 10 different basis functions, and then classified test image. After evaluating classification results, we tried to ascertain which basis function is the most effective for image classification. We also tried to see if the optimum basis function is decided by energy parameter before classifying the image using all basis function. The energy parameter of signal is the sum of the squares of wavelet coefficients. The energy parameter is calculated by sub-bands after the wavelet decomposition and the energy parameter of each sub-band can be a favorable feature of texture. The decision of optimum basis function using energy parameter in the wavelet based image classification is expected to be helpful for saving time and improving classification accuracy effectively.

• 대한수학회지
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• 제41권6호
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• pp.945-955
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• 2004

In this paper, we establish a number system in $R^n$ which arises from a Haar wavelet basis in connection with decompositions of certain Cuntz algebra representations on $L^2$( $R^n$). Number systems in $R^n$ are also of independent interest [9]. We study radix-representations of $\chi$ $\in$ $R^n$: $\chi$:$\alpha$$_{ι}$ $\alpha$$_{ι-1}$…$\alpha$$_1$$\alpha$$_{0}$ ㆍ$\alpha$$_{-1}$ $\alpha$$_{-2}$ … as $\chi$= $M^{ι}$$\alpha$$_{ι}$ $\alpha$＋…M$\alpha$$_1$＋$\alpha$$_{0}$ ＋ $M^{-1}$ $\alpha$$_{-1}$ ＋ $M^{-2}$ $\alpha$$_{-2}$ ＋… where each $\alpha$$_{k}$ $\in$ D, and D is some specified digit set. Our analysis uses iteration techniques of a number-theoretic flavor. The view-point is a dual one which we term fractals in the large vs. fractals in the small,illustrating the number theory of integral lattice points vs. fractions.s vs. fractions.