• Title/Summary/Keyword: Structure tensor

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REAL HYPERSURFACES WITH ξ-PARALLEL RICCI TENSOR IN A COMPLEX SPACE FORM

  • Ahn, Seong-Soo;Han, Seung-Gook;Kim, Nam-Gil;Lee, Seong-Baek
    • Communications of the Korean Mathematical Society
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    • v.13 no.4
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    • pp.825-838
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    • 1998
  • We prove that if a real hypersurface with constant mean curvature of a complex space form satisfying ▽$_{ξ/}$S = 0 and Sξ = $\sigma$ξ for a smooth function $\sigma$, then the structure vector field ξ is principal, where S denotes the Ricci tensor of the hypersurface.

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ON CHARACTERIZATIONS OF REAL HYPERSURFACES IN A COMPLEX SPACE FORM IN TERMS OF THE JACOBI OPERATORS

  • AHN, SEONG SOO;KIM, JONG CHUL
    • Honam Mathematical Journal
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    • v.26 no.2
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    • pp.155-161
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    • 2004
  • The shape operator or second fundamental tensor of a real hypersurface in $M_n(c)$ will be denoted by A, and the induced almost contact metric structure of the real hypersurface by (${\phi}$, <, >,${\xi}$, ${\eta}$). The purpose of this paper is to prove that is no ruled real hypersurface M in a complex space form $M_n(c)$, $c{\neq}0$, $n{\geq}3$, who satisfies $R_{\xi}{\phi}={\phi}R_{\xi}$ on M.

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SOME CHARACTERIZATIONS OF REAL HYPERSURFACES OF TYPE (A) IN A NONFLAT COMPLEX SPACE FORM

  • Ki, U-Hang;Liu, Hui-Li
    • Bulletin of the Korean Mathematical Society
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    • v.44 no.1
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    • pp.157-172
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    • 2007
  • In this paper, we prove that if the structure Jacobi operator $R_{\xi}-parallel\;and\;R_{\xi}$ commutes with the Ricci tensor S, then a real hypersurface with non-negative scalar curvature of a nonflat complex space form $M_{n}(C)$ is a Hopf hypersurface. Further, we characterize such Hopf hypersurface in $M_{n}(C)$.

An Improved Nonparametric Change Detection Algorithm Using Euler Number and Structure Tensor (오일러 수와 구조 텐서를 사용한 개선된 Nonparametric 변화 검출 알고리즘)

  • 이웅희;김태희;정동석
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.28 no.10C
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    • pp.958-966
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    • 2003
  • Change detection algorithms based on frame difference are frequently used for finding moving objects in image sequences. These algorithms detect the change of frames using estimated statistical background model. But, if this estimated background model is different from the actual statistical distribution, false detections are generated. In this paper, we propose an improved change detection algorithm using euler number and structure tensor. The proposed mapping method which is based on the euler number can be used for reducing the false detections that generated by nonparametric change detection algorithm. In this paper, the change in the region of moving object also can be detected by the proposed method using structure tensor. Experimental result shows that the proposed method reduces the false detections effectively by 90% on "Weather", by 34% on "Mother & daughter" and by 43% on "Aisle" than an existing method does.

COMMUTING STRUCTURE JACOBI OPERATOR FOR SEMI-INVARIANT SUBMANIFOLDS OF CODIMENSION 3 IN COMPLEX SPACE FORMS

  • KI, U-Hang;SONG, Hyunjung
    • East Asian mathematical journal
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    • v.38 no.5
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    • pp.549-581
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    • 2022
  • Let M be a semi-invariant submanifold with almost contact metric structure (𝜙, 𝜉, 𝜂, g) of codimension 3 in a complex space form Mn+1(c), c≠ 0. We denote by S and R𝜉 be the Ricci tensor of M and the structure Jacobi operator in the direction of the structure vector 𝜉, respectively. Suppose that the third fundamental form t satisfies dt(X, Y) = 2𝜃g(𝜙X, Y) for a certain scalar 𝜃(≠ 2c) and any vector fields X and Y on M. In this paper, we prove that M satisfies R𝜉S = SR𝜉 and at the same time R𝜉𝜙 = 𝜙R𝜉, then M is a Hopf hypersurface of type (A) provided that the scalar curvature s of M holds s - 2(n - 1)c ≤ 0.

Submanifolds of Codimension 3 in a Complex Space Form with Commuting Structure Jacobi Operator

  • Ki, U-Hang;Song, Hyunjung
    • Kyungpook Mathematical Journal
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    • v.62 no.1
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    • pp.133-166
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    • 2022
  • Let M be a semi-invariant submanifold with almost contact metric structure (𝜙, 𝜉, 𝜂, g) of codimension 3 in a complex space form Mn+1(c) for c ≠ 0. We denote by S and R𝜉 be the Ricci tensor of M and the structure Jacobi operator in the direction of the structure vector 𝜉, respectively. Suppose that the third fundamental form t satisfies dt(X, Y) = 2𝜃g(𝜙X, Y) for a certain scalar 𝜃 ≠ 2c and any vector fields X and Y on M. In this paper, we prove that if it satisfies R𝜉𝜙 = 𝜙R𝜉 and at the same time S𝜉 = g(S𝜉, 𝜉)𝜉, then M is a real hypersurface in Mn(c) (⊂ Mn+1(c)) provided that $\bar{r}-2(n-1)c{\leq}0$, where $\bar{r}$ denotes the scalar curvature of M.

REAL HYPERSURFACES IN THE COMPLEX HYPERBOLIC QUADRIC WITH CYCLIC PARALLEL STRUCTURE JACOBI OPERATOR

  • Jin Hong Kim;Hyunjin Lee;Young Jin Suh
    • Journal of the Korean Mathematical Society
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    • v.61 no.2
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    • pp.309-339
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    • 2024
  • Let M be a real hypersurface in the complex hyperbolic quadric Qm*, m ≥ 3. The Riemannian curvature tensor field R of M allows us to define a symmetric Jacobi operator with respect to the Reeb vector field ξ, which is called the structure Jacobi operator Rξ = R( · , ξ)ξ ∈ End(TM). On the other hand, in [20], Semmelmann showed that the cyclic parallelism is equivalent to the Killing property regarding any symmetric tensor. Motivated by his result above, in this paper we consider the cyclic parallelism of the structure Jacobi operator Rξ for a real hypersurface M in the complex hyperbolic quadric Qm*. Furthermore, we give a complete classification of Hopf real hypersurfaces in Qm* with such a property.

A Kalman Filter based Video Denoising Method Using Intensity and Structure Tensor

  • Liu, Yu;Zuo, Chenlin;Tan, Xin;Xiao, Huaxin;Zhang, Maojun
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.8 no.8
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    • pp.2866-2880
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    • 2014
  • We propose a video denoising method based on Kalman filter to reduce the noise in video sequences. Firstly, with the strong spatiotemporal correlations of neighboring frames, motion estimation is performed on video frames consisting of previous denoised frames and current noisy frame based on intensity and structure tensor. The current noisy frame is processed in temporal domain by using motion estimation result as the parameter in the Kalman filter, while it is also processed in spatial domain using the Wiener filter. Finally, by weighting the denoised frames from the Kalman and the Wiener filtering, a satisfactory result can be obtained. Experimental results show that the performance of our proposed method is competitive when compared with state-of-the-art video denoising algorithms based on both peak signal-to-noise-ratio and structural similarity evaluations.