Group theoretical methods in image processing
Group theoretical methods in image processing
Computation of component image velocity from local phase information
International Journal of Computer Vision
Phase-based disparity measurement
CVGIP: Image Understanding
The Design and Use of Steerable Filters
IEEE Transactions on Pattern Analysis and Machine Intelligence
IEEE Transactions on Pattern Analysis and Machine Intelligence
A lie group approach to steerable filters
Pattern Recognition Letters
Invariant geometric evolutions of surfaces and volumetric smoothing
SIAM Journal on Applied Mathematics
Design of Multiparameter Steerable Functions Using Cascade Basis Reduction
IEEE Transactions on Pattern Analysis and Machine Intelligence
Geometry-Driven Diffusion in Computer Vision
Geometry-Driven Diffusion in Computer Vision
Signal Processing for Computer Vision
Signal Processing for Computer Vision
Deformable Kernels for Early Vision
IEEE Transactions on Pattern Analysis and Machine Intelligence
ICCV '95 Proceedings of the Fifth International Conference on Computer Vision
Pyramidal implementation of deformable kernels
ICIP '95 Proceedings of the 1995 International Conference on Image Processing (Vol. 1)-Volume 1 - Volume 1
A Common Framework for Steerability, Motion Estimation and Invariant Feature Detection
A Common Framework for Steerability, Motion Estimation and Invariant Feature Detection
A Dynamic Scale–Space Paradigm
Journal of Mathematical Imaging and Vision
Representing Edge Models via Local Principal Component Analysis
ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
On steerability of Gabor-type filters for feature detection
Pattern Recognition Letters
IEEE Transactions on Pattern Analysis and Machine Intelligence
Wavelet steerability and the higher-order Riesz transform
IEEE Transactions on Image Processing
Approximate steerability of gabor filters for feature detection
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
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This paper describes a general mathematical formulation for theproblem of constructing steerable functions. The formulation is basedon Lie group theory and is thus applicable to transformationswhich are Lie groups, such as, rotation, translation, scaling,and affine transformation. For one-parameter and Abelianmulti-parameter Lie transformation groups, a canonical decompositionof all possible steerable functions, derived using the Jordandecomposition of matrices, is developed. It is shown thatany steerable function under Lie transformation groups can bedescribed using this decomposition. Finally, a catalog of steerablefunctions for several common multi-parameter image transformationgroups is also provided.