Steerable pyramid

Steerable pyramid toolbox. The Steerable Pyramid is a linear multi-scale, multi-orientation image decomposition that provides a useful front-end for image-processing and computer vision applications. We developed this representation in 1990, in order to overcome the limitations of orthogonal separable wavelet decompositions that were then becoming popular for image processing (specifically, those representations are heavily aliased, and do not represent oblique orientations well). Once the orthogonality constraint is dropped, it makes sense to completely reconsider the filter design problem (as opposed to just re-using orthogonal wavelet filters in a redundant representation, as is done in cycle-spinning or undecimated wavelet transforms!). Detailed information may be found in the references listed below.


References in zbMATH (referenced in 61 articles )

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  1. Wang, Yi-Qing: A note on the size of denoising neural networks (2016)
  2. Alvarez, Luis; Gousseau, Yann; Morel, Jean-Michel; Salgado, Agustín: Exploring the space of abstract textures by principles and random sampling (2015)
  3. Chamorro-Martínez, Jesús; Martínez-Jiménez, Pedro Manuel; Soto-Hidalgo, José Manuel; Prados-Suárez, Belén: Fuzzy sets on 2D spaces for fineness representation (2015)
  4. Han, Zhi; Xu, Zongben; Zhu, Song-Chun: Video primal sketch: a unified middle-level representation for video (2015)
  5. Tartavel, Guillaume; Gousseau, Yann; Peyré, Gabriel: Variational texture synthesis with sparsity and spectrum constraints (2015)
  6. Chamorro-Martínez, Jesús; Martínez-Jiménez, Pedro Manuel; Soto-Hidalgo, José Manuel; Prados-Suárez, Belén: Perception-based fuzzy sets for visual texture modelling (2014)
  7. Lyu, Siwei; Pan, Xunyu; Zhang, Xing: Exposing region splicing forgeries with blind local noise estimation (2014)
  8. Ward, John Paul; Unser, Michael: Harmonic singular integrals and steerable wavelets in $L_2(\mathbb R^d)$ (2014)
  9. Haddad, Zehira; Beghdadi, Azeddine; Serir, Amina; Mokraoui, Anissa: Wave atoms based compression method for fingerprint images (2013)
  10. Nikolova, Mila; Wen, You-Wei; Chan, Raymond: Exact histogram specification for digital images using a variational approach (2013)
  11. Unser, Michael; Chenouard, Nicolas: A unifying parametric framework for 2D steerable wavelet transforms (2013)
  12. Andersson, Fredrik; Carlsson, Marcus; Tenorio, Luis: On the representation of functions with Gaussian wave packets (2012)
  13. Barri, Adriaan; Dooms, Ann; Schelkens, Peter: The near shift-invariance of the dual-tree complex wavelet transform revisited (2012)
  14. Hsin, Hsi Chin; Sung, Tze-Yun; Shieh, Yaw-Shih; Cattani, Carlo: A new texture synthesis algorithm based on wavelet packet tree (2012)
  15. Rajpoot, Nasir; Butt, Irfan: A multiresolution framework for local similarity based image denoising (2012)
  16. Bertero, M.; Boccacci, P.; La Camera, A.; Olivieri, C.; Carbillet, M.: Imaging with LINC-NIRVANA, the Fizeau interferometer of the large binocular telescope: state of the art and open problems (2011)
  17. Chainais, Pierre; Koenig, Émilie; Delouille, Véronique; Hochedez, Jean-François: Virtual super resolution of scale invariant textured images using multifractal stochastic processes (2011)
  18. Elguebaly, Tarek; Bouguila, Nizar: Bayesian learning of finite generalized Gaussian mixture models on images (2011)
  19. Han, Shoudong; Tao, Wenbing; Wu, Xianglin: Texture segmentation using independent-scale component-wise Riemannian-covariance Gaussian mixture model in KL measure based multi-scale nonlinear structure tensor space (2011)
  20. Lyu, Siwei: Dependency reduction with divisive normalization: justification and effectiveness (2011)

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