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Stability of Phase Information
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ECCV '02 Proceedings of the 7th European Conference on Computer Vision-Part I
The Monogenic Scale-Space: A Unifying Approach to Phase-Based Image Processing in Scale-Space
Journal of Mathematical Imaging and Vision
Distinctive Image Features from Scale-Invariant Keypoints
International Journal of Computer Vision
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CVPR '06 Proceedings of the 2006 IEEE Computer Society Conference on Computer Vision and Pattern Recognition - Volume 2
2D Image Analysis by Generalized Hilbert Transforms in Conformal Space
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Geometric Algebra with Applications in Engineering
Geometric Algebra with Applications in Engineering
Dense optical flow estimation from the monogenic curvature tensor
SSVM'07 Proceedings of the 1st international conference on Scale space and variational methods in computer vision
Phase-Based registration of multi-view real-time three-dimensional echocardiographic sequences
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Adaptive multiscale ultrasound compounding using phase information
MICCAI'05 Proceedings of the 8th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part I
Hybrid matrix geometric algebra
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IEEE Transactions on Signal Processing
Image Analysis by Conformal Embedding
Journal of Mathematical Imaging and Vision
Phase congruency induced local features for finger-knuckle-print recognition
Pattern Recognition
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This work covers a fundamental problem of local phase based image analysis: the isotropic generalization of the classical 1D analytic signal to two dimensions. The analytic signal enables the analysis of local phase and amplitude information of 1D signals. Local phase, amplitude and additional orientation information can be extracted by the 2D monogenic signal with the restriction to intrinsically 1D signals. In case of 2D image signals the monogenic signal enables the rotationally invariant analysis of lines and edges. In this work we present the 2D analytic signal as a novel generalization of both the analytic signal and the 2D monogenic signal. In case of 2D image signals the 2D analytic signal enables the isotropic analysis of lines, edges, corners and junctions in one unified framework. Furthermore, we show that 2D signals are defined on a 3D projective subspace of the homogeneous conformal space which delivers a descriptive geometric interpretation of signals providing new insights on the relation of geometry and 2D image signals. Finally, we will introduce a novel algebraic signal representation, which can be regarded as an alternative and fully isomorphic representation to classical matrices and tensors. We will show the solution of isotropic intrinsically 2D image analysis without the need of steering techniques.