The contourlet transform:an ef cient directional multiresolution image representation

By M. N. Do, Martin Vetterli. 2003

760 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/63d24da1f247db631b7feb8cedcec1d407aa6cb1

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Citations in the corpus

Transforms and Operators for Directional Bioimage Analysis: A Survey. (2016, background): “2009; Kutyniok and Labate 2012), and contourlets (Do and Vetterli 2005) have attracted a lot of interest.”
Local adaptivity to variable smoothness for exemplar-based image denoising and representation (2005, unknown): “However, we do not draw into comparison both the wavelet-based methods [24, 74, 62, 22, 60, 47] since they process the input data in the transformed domain, and the fractal denoising methods [32] also rooted in wavelet theory.”
Wavelets with composite dilations and their MRA properties (2006, background): “…representation systems which have exactly the features we have described, as well as several other properties which are closely analogous to the properties of systems constructed in [7], and, therefore, for the reasons explained there as well as in [4] [5] [8], have great potential in applications.”
Full length article: Compactly supported shearlets are optimally sparse (2011, unknown): “For the precise definition of directional vanishing moments, we refer to [4].”
Sparse directional image representations using the discrete shearlet transform (2008, background): “Also the discrete construction of the contourlets introduced by Do and Vetterli [12] has the intent to provide a partition of the frequency plane very similar to the one represented in Figure 1.”
The Cosparse Analysis Model and Algorithms (2011, unknown): “In signal and image processing, discrete transforms such as wavelet, Gabor, curvelet, contourlet, shearlet, and others [33, 39, 13, 27], are of interest, and this empirical observation seems to give a good support for the sparse synthesis model.”
Optimally Sparse Multidimensional Representation Using Shearlets (2007, background): “Those include contourlets , complex wavelets and other “directional wavelets” in the ﬁlter bank literature [1, 2, 11, 20, 24, 26], as well as brushlets [8], ridgelets [5], curvelets [7] and bandelets [22].”
Directionlets: anisotropic multidirectional representation with separable filtering (2006, background): “We show that our transform has good approximation properties (see also [38]) as compared to the approximation achieved by some other overcomplete transform constructions [11]–[21] and is superior to the performance of the standard separable 2-D WT having the same complexity.”