On the Axioms of Scale Space Theory

We consider alternative scale space representations beyond the well-established Gaussian case that satisfy all “reasonable” axioms. One of these turns out to be subject to a first order pseudo partial differential equation equivalent to the Laplace equation on the upper half plane {(x, s) ∈ ℝd × ℝ | s > 0}. We investigate this so-called Poisson scale space and show that it is indeed a viable alternative to Gaussian scale space. Poisson and Gaussian scale space are related via a one-parameter class of operationally well-defined intermediate representations generated by a fractional power of (minus) the spatial Laplace operator.

[1]  Joachim Weickert,et al.  Anisotropic diffusion in image processing , 1996 .

[2]  Joachim Weickert,et al.  Scale-Space Theories in Computer Vision , 1999, Lecture Notes in Computer Science.

[3]  Luc Florack,et al.  A Geometric Model for Cortical Magnification , 2000, Biologically Motivated Computer Vision.

[4]  Michael Felsberg,et al.  The Monogenic Scale Space on a Bounded Domain and Its Applications , 2003, Scale-Space.

[5]  Luc Van Gool,et al.  An Extended Class of Scale-Invariant and Recursive Scale Space Filters , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  P. Lions,et al.  Axioms and fundamental equations of image processing , 1993 .

[7]  J. Gilbert,et al.  Clifford Algebras and Dirac Operators in Harmonic Analysis , 1991 .

[8]  Wiro J. Niessen,et al.  Pseudo-Linear Scale-Space Theory , 2004, International Journal of Computer Vision.

[9]  Tony Lindeberg,et al.  Scale-Space Theory in Computer Vision , 1993, Lecture Notes in Computer Science.

[10]  Max A. Viergever,et al.  Scale-Space Theory in Computer Vision , 1997 .

[11]  Michael Felsberg,et al.  The Monogenic Scale-Space: A Unifying Approach to Phase-Based Image Processing in Scale-Space , 2004, Journal of Mathematical Imaging and Vision.

[12]  Michael Felsberg,et al.  Low-level image processing with the structure multivector , 2002 .

[13]  Michael Felsberg,et al.  Scale Adaptive Filtering Derived from the Laplace Equation , 2001, DAGM-Symposium.

[14]  C. W. Groetsch,et al.  Elements of applicable functional analysis , 1980 .

[15]  M. Felsberg,et al.  α Scale Spaces on a Bounded Domain , 2003 .

[16]  C. Chitti Babu,et al.  On feature extraction in pattern recognition , 1972, Inf. Sci..

[17]  de J Jan Graaf,et al.  A theory of generalized functions based on holomorphic semi-groups: Part C: Linear mappings, tensor products and kernel theorems , 1983 .

[18]  Michael Kerckhove,et al.  Scale-Space and Morphology in Computer Vision , 2001, Lecture Notes in Computer Science 2106.

[19]  Peter Johansen,et al.  Gaussian Scale-Space Theory , 1997, Computational Imaging and Vision.

[20]  Luc Florack,et al.  Image Structure , 1997, Computational Imaging and Vision.

[21]  Max A. Viergever,et al.  Nonlinear scale-space , 1995, Image Vis. Comput..

[22]  Derek W. Robinson,et al.  Elliptic Operators and Lie Groups , 1991 .

[23]  A. V. Balakrishnan,et al.  Fractional powers of closed operators and the semigroups generated by them. , 1960 .

[24]  Tony Lindeberg,et al.  Scale-Space for Discrete Signals , 1990, IEEE Trans. Pattern Anal. Mach. Intell..

[25]  Atsushi Imiya,et al.  On the History of Gaussian Scale-Space Axiomatics , 1997, Gaussian Scale-Space Theory.

[26]  de J Jan Graaf A theory of generalized functions based on holomorphic semi-groups : part B : analyticity spaces, trajectory spaces and their pairing , 1979 .

[27]  J. Koenderink The structure of images , 2004, Biological Cybernetics.

[28]  M. Felsberg,et al.  The Poisson Scale-Space: A Unified Approach to Phase-Based Image Processing in Scale-Space , 2002 .

[29]  R. G. Cooke Functional Analysis and Semi-Groups , 1949, Nature.