• Title/Summary/Keyword: 제곱근 연산자

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Suggestion for a splitting technique of the square-root operator of three dimensional acoustic parabolic equation based on two variable rational approximant with a factored denominator (인수분해 된 분모를 갖는 두 변수 유리함수 근사에 기반한 3차원 음향 포물선 방정식 제곱근 연산자의 분할기법 제안)

  • Lee, Keunhwa
    • The Journal of the Acoustical Society of Korea
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    • v.36 no.1
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    • pp.1-11
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    • 2017
  • In this study, novel approximate form of the square-root operator of three dimensional acoustic Parabolic Equation (3D PE) is proposed using a rational approximant for two variables. This form has two advantages in comparison with existing approximation studies of the square-root operator. One is the wide-angle capability. The proposed form has wider angle accuracy to the inclination angle of ${\pm}62^{\circ}$ from the range axis of 3D PE at the bearing angle of $45^{\circ}$, which is approximately three times the angle limit of the existing 3D PE algorithm. Another is that the denominator of our approximate form can be expressed into the product of one-dimensional operators for depth and cross-range. Such a splitting form is very preferable in the numerical analysis in that the 3D PE can be easily transformed into the tridiagonal matrix equation. To confirm the capability of the proposed approximate form, comparative study of other approximation methods is conducted based on the phase error analysis, and the proposed method shows best performance.

Shape From Focus Algorithm with Optimization of Focus Measure for Cell Image (초점 연산자의 최적화를 통한 세포영상의 삼차원 형상 복원 알고리즘)

  • Lee, Ik-Hyun;Choi, Tae-Sun
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.3 no.3
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    • pp.8-13
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    • 2010
  • Shape form focus (SFF) is a technique that reconstructs 3D shape of an object using image focus. Although many SFF methods have been proposed, there are still notable inaccuracy effects due to noise and non-optimization of image characteristics. In this paper, we propose a noise filter technique for noise reduction and genetic algorithm (GA) for focus measure optimization. The proposed method is analyzed with a statistical criteria such as Root Mean Square Error (RMSE) and correlation.

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