The lifting scheme: a construction of second generation wavelets

By Wim Sweldens. 1998

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Yoshua Bengio
2. Dacheng Tao
3. Jiashi Feng
4. Luc Van Gool
5. Yi Yang
6. Trevor Darrell
7. Kaiming He
8. Andrea Vedaldi

Citations in the corpus

• i-RevNet: Deep Invertible Networks (2018, methodology): “All these architectures are similar to the lifting scheme (Sweldens, 1998) and Feistel cipher diagrams (Menezes et al., 1996), as we will show.”
• The emerging field of signal processing on graphs: Extending high-dimensional data analysis to networks and other irregular domains (2012, positive): “Lifting based transforms for graphs [49], [61], [62] are extensions of the lifting wavelets originally proposed for 1D signals by Sweldens [63].”
• Normal Multiresolution Approximation of Curves (2004, background): “We can now think of this as a wavelet transformation similar to the notion of lifting [18].”
• Multiresolution signal processing for meshes (1999, methodology): “e, critically sampled multiresolution transform based on the Lifting scheme [25].”
• Generalized Tree-Based Wavelet Transform (2010, methodology): “These methods employ pairing or reordering of wavelet coefficients in the decomposition schemes in order to adapt to their input images.”
• Wavelet analysis of ecological time series (2008, methodology): “As regards awkward sampling quality, Keitt and Fischer (2006), analyzing the response of zooplankton communities to anthropogenic disturbance, employed an adaptive ''second-generation'' wavelet named the ''lifting scheme'' (Sweldens 1998).”
• Reversible Image Watermarking Based on Integer-to-Integer Wavelet Transform (2007, methodology): “To avoid this problem, an invertible integer-to-integer wavelet transform based on lifting is used in the proposed scheme [23]-[25].”
• Commutation for Irregular Subdivision (2001, background): “Rather they are instances of so-called second-generation wavelets [17].”
• The second-generation wavelet transform and its application in denoising of seismic data (2005, background): “an integer to integer wavelet transforms (Sweldens, 1997; Donoho, 1995; Sweldens, 1998 ).”
• Wavelets on Graphs via Deep Learning (2013, methodology): “Our construction of wavelets is based on the lifting scheme [23].”