Results 241 to 250 of about 9,624,872 (292)

Nonlinear Scale-Space

Image and Vision Computing, 1994
A generalization of linear Gaussian scale-space theory for scalar images is proposed, based on a particular type of metric transform preserving the intrinsic properties of the spatial domain. The existence of such a transformation defines an equivalence class.
Luc Florack   +4 more
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SCALES OF BANACH SPACES

Russian Mathematical Surveys, 1966
CONTENTSIntroduction § 1. Scales of Banach spaces § 2. Normal embeddings of spaces and of their duals § 3. Normal scale of spaces. Related spaces § 4. Interpolation properties. Minimal and maximal scales § 5. The Holder scale § 6. The Marcinkiewicz scale § 7. Analytic scales § 8. Spaces of means § 9. Hilbert scalesAddendum: Yu. I. Petunin. A non-linear
Kreĭn, S. G., Petunin, Yu. I.
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Linear scale-space

Journal of Mathematical Imaging and Vision, 1994
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Luc Florack   +3 more
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Morphological scale-space

Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol. IV. Conference D: Architectures for Vision and Pattern Recognition,, 1997
Two scaled morphological operations, the multiscale dilation-erosion and the multiscale closing-opening, have been introduced for the scale-space smoothing of signals. The multiscale operations are translation invariant, nonlinear, increasing, and dependent on a real-scale parameter, which can be negative.
openaire   +7 more sources

Temporal Scale Spaces

International Journal of Computer Vision, 2003
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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The Bessel Scale-Space

2005
In this paper we propose a novel type of scales-spaces which is emerging from the family of inhomogeneous pseudodifferential equations $(I - \tau\Delta)^{\frac{t}{2}}u$ with τ ≥ 0 and scale parameter t ≥ 0. Since they are connected to the convolution semi-group of Bessel potentials we call the associated operators {R$^{n}_{t,{ \tau}}$ | 0≤ τ,t} either ...
Bernhard Burgeth   +2 more
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Dyadic scale space

Pattern Recognition, 1996
In this paper, we first approximate the Gaussian function with any scale by the linear finite combination of Gaussian functions with dyadic scale; consequently, the scale space can be constructed much more efficiently: we only perform smoothing at these dyadic scales and the smoothed signals at other scales can be found by calculating linear ...
Ge Cong, Songde Ma
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