Fast discrete curvelet transforms

被引:1647
|
作者
Candes, Emmanuel [1 ]
Demanet, Laurent
Donoho, David
Ying, Lexing
机构
[1] CALTECH, Pasadena, CA 91125 USA
[2] Stanford Univ, Dept Stat, Stanford, CA 94305 USA
来源
MULTISCALE MODELING & SIMULATION | 2006年 / 5卷 / 03期
关键词
two-dimensional and three-dimensional curvelet transforms; fast Fourier transforms; unequally spaced fast Fourier transforms; smooth partitioning; interpolation; digital shear; filtering; wrapping;
D O I
10.1137/05064182X
中图分类号
O1 [数学];
学科分类号
0701 ; 070101 ;
摘要
This paper describes two digital implementations of a new mathematical transform, namely, the second generation curvelet transform in two and three dimensions. The first digital transformation is based on unequally spaced fast Fourier transforms, while the second is based on the wrapping of specially selected Fourier samples. The two implementations essentially differ by the choice of spatial grid used to translate curvelets at each scale and angle. Both digital transformations return a table of digital curvelet coefficients indexed by a scale parameter, an orientation parameter, and a spatial location parameter. And both implementations are fast in the sense that they run in O(n(2) log n) flops for n by n Cartesian arrays; in addition, they are also invertible, with rapid inversion algorithms of about the same complexity. Our digital transformations improve upon earlier implementations - based upon the first generation of curvelets - in the sense that they are conceptually simpler, faster, and far less redundant. The software CurveLab, which implements both transforms presented in this paper, is available at http:// www.curvelet.org.
引用
收藏
页码:861 / 899
页数:39
相关论文
共 50 条
  • [21] Fast computation of the discrete Walsh and Hadamard transforms
    Concordia Univ, Montreal, Canada
    IEEE Trans Image Process, 6 (898-904):
  • [22] Automatic generation of fast discrete signal transforms
    Egner, S
    Püschel, M
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2001, 49 (09) : 1992 - 2002
  • [23] UNIFIED TREATMENT OF DISCRETE FAST UNITARY TRANSFORMS
    FINO, BJ
    ALGAZI, VR
    SIAM JOURNAL ON COMPUTING, 1977, 6 (04) : 700 - 717
  • [24] Matrix Factorization and Some Fast Discrete Transforms
    Bouyukliev, Iliya
    Dzhumalieva-Stoeva, Mariya
    Piperkov, Paskal
    AXIOMS, 2024, 13 (08)
  • [25] Seismic data denoising using curvelet transforms and fast non-local means
    Zhao, Siwei
    Iqbal, Ibrar
    Yin, Xiaokang
    Zhang, Tianyu
    Jia, Mingkun
    Chen, Meng
    PETROLEUM SCIENCE AND TECHNOLOGY, 2024, 42 (05) : 581 - 596
  • [26] Ceramic microscopic image processing based on fast discrete curvelet transform
    Li, Qing-Wu
    Liu, Guo-Gao
    2007 INTERNATIONAL CONFERENCE ON WAVELET ANALYSIS AND PATTERN RECOGNITION, VOLS 1-4, PROCEEDINGS, 2007, : 344 - 349
  • [27] Moment-based fast discrete sine transforms
    Liu, JG
    Chan, FHY
    Lam, FK
    Li, HF
    IEEE SIGNAL PROCESSING LETTERS, 2000, 7 (08) : 227 - 229
  • [28] Fast algorithms for the computation of sliding discrete sinusoidal transforms
    Kober, V
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2004, 52 (06) : 1704 - 1710
  • [29] SPREADSHEET DEMONSTRATIONS OF DISCRETE AND FAST FOURIER-TRANSFORMS
    CHAPMAN, D
    INTERNATIONAL JOURNAL OF ELECTRICAL ENGINEERING EDUCATION, 1993, 30 (03) : 211 - 215
  • [30] Fast discrete W transforms via computation of moments
    Liu, JG
    Liu, YZ
    Wang, GY
    IEEE TRANSACTIONS ON SIGNAL PROCESSING, 2005, 53 (02) : 654 - 659