期刊
SIAM JOURNAL ON IMAGING SCIENCES
卷 7, 期 1, 页码 157-186出版社
SIAM PUBLICATIONS
DOI: 10.1137/130923774
关键词
empirical wavelets; image processing; Littlewood-Paley wavelet; ridgelet; curvelet
类别
资金
- NSF [DMS-0914856, DMS-1118971]
- ONR [N00014-08-1-1119, N0014-09-1-0360]
- ONR MURI USC
- UC Lab Fees Research
- Keck Foundation
A recently developed approach, called empirical wavelet transform, aims to build one-dimensional (1D) adaptive wavelet frames accordingly to the analyzed signal. In this paper, we present several extensions of this approach to two-dimensional (2D) signals (images). We revisit some well-known transforms (tensor wavelets, Littlewood-Paley wavelets, ridgelets, and curvelets) and show that it is possible to build their empirical counterparts. We prove that such constructions lead to different adaptive frames which show some promising properties for image analysis and processing.
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