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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.
Max A. Viergever +4 more
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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.
Max A. Viergever +4 more
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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 ...
Songde Ma, Ge Cong
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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 ...
Songde Ma, Ge Cong
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Journal of Mathematical Imaging and Vision, 1994
The formulation of afront-end orearly vision system is addressed, and its connection with scale-space is shown. A front-end vision system is designed to establish a convenient format of some sampled scalar field, which is suited for postprocessing by various dedicated routines.
Jan J. Koenderink +3 more
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The formulation of afront-end orearly vision system is addressed, and its connection with scale-space is shown. A front-end vision system is designed to establish a convenient format of some sampled scalar field, which is suited for postprocessing by various dedicated routines.
Jan J. Koenderink +3 more
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Spaces and scales of innovation
Progress in Human Geography, 2001Contemporary research on innovative processes makes use of a range of scales, from the global to the regional/local. In addition, network-based approaches have introduced a nonterritorially bounded dimension to studies of innovation. While much of the latter has, to date, been concerned with local networks, recent work has pointed to the importance of
Bunnell, T.G., Coe, N.M.
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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
S G Krein, Yu. I. Petunin
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Proceedings., 11th IAPR International Conference on Pattern Recognition. Vol. IV. Conference D: Architectures for Vision and Pattern Recognition,, 1997
Scale-space is an important recent concept used in image processing and pattern recognition. Traditional scale-space is generated by a linear smoothing operation. The author presents a nonlinear type of smoother related to mathematical morphology which meets (modified) 'scale-space axioms' and also generates a 'scale-space'.
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Scale-space is an important recent concept used in image processing and pattern recognition. Traditional scale-space is generated by a linear smoothing operation. The author presents a nonlinear type of smoother related to mathematical morphology which meets (modified) 'scale-space axioms' and also generates a 'scale-space'.
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2019
We introduce a novel scale-space concept that is inspired by inpainting-based lossy image compression and the recent denoising by inpainting method of Adam et al. (2017). In the discrete setting, the main idea behind these so-called sparsification scale-spaces is as follows: Starting with the original image, one subsequently removes a pixel until a ...
Cárdenas, Marcelo +2 more
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We introduce a novel scale-space concept that is inspired by inpainting-based lossy image compression and the recent denoising by inpainting method of Adam et al. (2017). In the discrete setting, the main idea behind these so-called sparsification scale-spaces is as follows: Starting with the original image, one subsequently removes a pixel until a ...
Cárdenas, Marcelo +2 more
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From Gaussian scale-space to B-spline scale-space
1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258), 1999The Gaussian kernel has long been used in the classical multiscale analysis. The purpose of the paper is to propose the uniform B-spline as an alternative for the visual modeling. A general framework for various scale-space representations is formulated using the B-spline approach.
Wang, Yu-Ping, Lee, S.L.
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Laplacian Scale-Space Behavior of Planar Curve Corners
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2015Scale-space behavior of corners is important for developing an efficient corner detection algorithm. In this paper, we analyze the scale-space behavior with the Laplacian of Gaussian (LoG) operator on a planar curve which constructs Laplacian Scale Space
Xiaohong Zhang +4 more
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International Journal of Computer Vision, 2003
In this paper we discuss how to define a scale space suitable for temporal measurements. We argue that such a temporal scale space should possess the properties of: temporal causality, linearity, continuity, positivity, recursitivity as well as translational and scaling covariance.
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In this paper we discuss how to define a scale space suitable for temporal measurements. We argue that such a temporal scale space should possess the properties of: temporal causality, linearity, continuity, positivity, recursitivity as well as translational and scaling covariance.
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