Advanced Search
Volume 20 Issue 1
Jan.  1998
Turn off MathJax
Article Contents
Zheng Zhi-Dong, Yuan Hong-Gang, Zhang Jian-Yun. Multitarget Localization Based on Sparse Representation for Bistatic MIMO Radar in the Presence of Impulsive Noise[J]. Journal of Electronics & Information Technology, 2014, 36(12): 3001-3007. doi: 10.3724/SP.J.1146.2013.01861
Citation: Tang Xianghong, Gong Yu, Gong Yaohuan, Gu Deren. APPLICATION OF M-BAND WAVELET TRANSFORM TO IMAGES[J]. Journal of Electronics & Information Technology, 1998, 20(1): 7-13.

APPLICATION OF M-BAND WAVELET TRANSFORM TO IMAGES

  • Received Date: 1996-07-10
  • Rev Recd Date: 1997-03-17
  • Publish Date: 1998-01-19
  • Wavelet transform, especially the multiresolution representation, is a very effective tool for analyzing the information contents of a signal. Based on Mallat s multiresolution analysis, this paper discusses the theoretical analysis of M-band multiresolution signal decomposition, proposes a new algorithm for realizing the theory, studies the properties of an operator which approximates a signal at a given resolution, and applies the theory to images. The results show that, first, images can be decomposed and reconstructed by M-band multiresolution representation; second, the edges of image can be detected by M-band wavelet transform.
  • Jawerth B Sweldens W. An overview of wavelet based multiresolution analysis[J].SIAM.1994, 36(3):377-412[2][2][3]Daubechines I. Orthonormal bases of compactly supported wavelet[J].Commu. Pure Appl.1988, 41(2):909-996[4]Mallat S G. Multifrequency channel decompositions of images and wavelet models[J].IEEE Trans. on ASSP.1989, 37(12):2091-2110[5]Zou hI, Tewfik A H. Discrete orthogonal M-band wavelet decomposition. In proc. ICASSP, San. Franciso: 1992, 4(iv): 605-608.[6]Steffen P, Heller P N, Gopinuth R A. Theory of regular M-band wavelet bases[J].IEEE Trans. on SP.1993, 41(12):3497-3511[7]Mallat S G. A theory for multiresolution signal decomposition: The wavelet representation. IEEE Trans. on PAMI, 1989, 11(11): 674-693.[8]Mallat S G. Characterization of signals from multiscale edges. IEEE trans. PAMI, 1992, 14(7): 710-732.[9]马尔D著,姚国正,等译.视觉计算理论.北京:科学出版社,1988, 40-281.[10]Ikonomopouls A, Kunt M. High compression image coding via directonal filtering. Signal Processing, 1985; 8(1): 179-203.
  • Cited by

    Periodical cited type(8)

    1. 毛毅,段永胜,黄中瑞,张峻宁. 一种在脉冲噪声环境下的最大相关熵目标直接定位算法. 系统工程与电子技术. 2023(09): 2651-2658 .
    2. 何孔飞,熊鹏文,童小宝. 一种基于联合组核稀疏编码的多模态材料感知与识别方法. 中国测试. 2020(12): 129-134 .
    3. 赵智昊,陈松,顾帅楠. 基于改进RPCA的双基地MIMO雷达参数估计方法. 信息工程大学学报. 2018(02): 166-172 .
    4. 赵智昊,吕品品,秦文利. 基于QR-RPCA的双基地MIMO雷达参数估计方法. 太赫兹科学与电子信息学报. 2018(02): 259-265 .
    5. 陈显舟,杨旭,陈周,白琳,方海. 双基地多输入多输出雷达收发四维角联合估计. 兵工学报. 2017(05): 917-923 .
    6. 黄中瑞,单凉,陈明建,张剑云. 一种新的MIMO雷达发射波形设计方法. 电子与信息学报. 2016(05): 1026-1033 . 本站查看
    7. 李丽,邱天爽. 冲激噪声环境下基于最大相关熵准则的双基地MIMO雷达目标参数联合估计算法. 电子与信息学报. 2016(12): 3189-3196 . 本站查看
    8. 李永潮,刁鸣. 单基地MIMO雷达的非圆信号DOA估计. 应用科技. 2016(01): 5-8 .

    Other cited types(6)

  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索

    Article Metrics

    Article views (2049) PDF downloads(373) Cited by()
    Proportional views
    Related

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return