Titlebook: Scale-Space Theory in Computer Vision; First International Bart Haar Romeny,Luc Florack,Max Viergever Conference proceedings 1997 Springer

stress-response

适宜

Linear spatio-temporal scale-space,y convolution with a semi-group of filter kernels and that (ii) local extrema must not be enhanced when the scale parameter increases, a complete taxonomy is given of the linear scale-space concepts that satisfy these conditions on spatial, temporal and spatio-temporal domains, including the cases w

Stress-Fracture

Following feature lines across scale,arching Lines that allows us to search for iso-surfaces and their intersections in spaces of arbitrary dimension. Specifically, we have implemented a 4D extension that we apply to track lines efficiently on iso-surfaces. We show that it automatically finds the connection order of singularities. As a

regale

A multi-scale line filter with automatic scale selection based on the Hessian matrix for medical imnd on the eigenvector analysis of the Hessian matrix. The method allows for the estimation of the local diameter, the longitudinal direction and the contrast of line-structures and for the distinction between edge-like and line-like structures. The characteristics of the method in respect to several

流逝

Supervised diffusion parameter selection for filtering SPECT brain images,rs. This is often accomplished by stopping the iteration process at a relatively low number of iterations or by post filtering the reconstructed image. The aim of this paper is to investigate whether stopping is better than post-filtering, and to determine suitable filter functions for Single Photon

易于

Image loci are ridges in geometric spaces, the extension parameters being directions and aperture. We define the notion of a height ridge and show how height ridges have been used by other authors. We also provide a catalog of useful variations of the basic definition. We then show the generic behavior of the maximal convexity form of ridge

Individual

钝剑

Scale space analysis by stabilized inverse diffusion equations,r applicability in image processing. An equation belonging to this family is an inverse diffusion everywhere except at local extrema, where some stabilization is introduced. For this reason, we call these equations “stabilized inverse diffusion equations” (“SIDEs”). A SIDE in one spatial dimension m

gonioscopy

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