Abstract
An efficient architecture is presented to synthesize filters of arbitrary orientations from linear combinations of basis filters, allowing one to adaptively 'steer' a filter to any orientation, and to determine analytically the filter output as a function of orientation. The authors show how to design and steer filters, and present examples of their use in several tasks: the analysis of orientation and phase, angularly adaptive filtering, edge detection, and shape-from-shading. It is also possible to build a self-similar steerable pyramid representation which may be considered to be a steerable wavelet transform. The same concepts can be generalized to the design of 3-D steerable filters, which should be useful in the analysis of image sequences and volumetric data.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">></ETX>
Keywords
Computer visionOrientation (vector space)Artificial intelligencePyramid (geometry)Filter (signal processing)Computer scienceWaveletWavelet transformBasis (linear algebra)Representation (politics)Image (mathematics)Composite image filterAdaptive filterAlgorithmMathematics
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Publication Info
- Year
- 2002
- Type
- article
- Pages
- 406-415
- Citations
- 51
- Access
- Closed
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Cite This
William T. Freeman,
Edward H. Adelson
(2002).
Steerable filters for early vision, image analysis, and wavelet decomposition.
, 406-415.
https://doi.org/10.1109/iccv.1990.139562
Identifiers
- DOI
- 10.1109/iccv.1990.139562