多维信号的微局部奇异方向检测
Detection of Microlocal Singularity Directions of Multi-dimensional Signals
-
摘要: 多维信号的奇异性方向检测在许多领域都有重要的应用。在微局部分析的意义下,可以将图像的边缘和奇异性方向看作波前集。该文从工程角度对此给出一个比较直观的解释,并且基于此提出了一个自动检测多重奇异性方向的算法,可用于图像分析和多维信号检测等多个领域。Abstract: Detecting singularities of multi-dimensional signals is important and interesting in various fields. The edge of an image and the directions of singularity can be regarded as a wavefront set in the meaning of microlocal analysis, which is intuitively illustrated from the viewpoint of engineering in this paper. A wavefront detection algorithm is proposed, which is based on microlocal analysis and can be applied to image analysis, multi-dimensional signal detection and many other related fields. Experimental results indicate that this algorithm is simple and successful.
-
Martin H. Efficient One-, Two- and Multidimensional High-Resolution Array Signal Processing.Aachen: Shaker Verlag, 1997: 9-57.[2]Margaret C. Synthetic Aperture Radar (SAR) and Microlocal Analysis, Dept. of Mathematical Sciences, Rensselaer Polytechnic Institute, March 2002.[3]Margaret C. A mathematical tutorial on synthetic aperture radar[J].SIAM Review.2001, 43(2):301-312[4]Ashino R, Heil C, Nagase M, Vaillancourt R. Microlocal filtering with multiwavelets[J].Computers and Mathematics with Applications.2001, 41:111-133[5]王桥,吴乐南.方向正交小波基与信号的方向性分析.应用科学学报,2000,18(1):76-79. ［6］齐民友.线性偏微分算子引论(上)[M].北京,科学出版社,1984:508-518.[6]Popivanov P R, Iordanov I V. Paradifferential operators and propagation of singularities for nonlinear P. D. E.. Akademic der Wissenschaften dev DDR. Institut fur Mathematile, 1983.[7]Hyvarinen A. Survey on independent component analysis. Neural Computing Surveys, 1999, 2:94-128. -
计量
- 文章访问数: 2376
- HTML全文浏览量: 108
- PDF下载量: 664
- 被引次数: 0
下载:
