The Computation of Visible-Surface Representations
IEEE Transactions on Pattern Analysis and Machine Intelligence
Triangular NURBS surface modeling of scattered data
Proceedings of the 7th conference on Visualization '96
Topographic Maps and Local Contrast Changes in Natural Images
International Journal of Computer Vision
International Journal of Computer Vision - Special issue on computer vision research at NEC Research Institute
Edge, Junction, and Corner Detection Using Color Distributions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Where and Why Local Shading Analysis Works
IEEE Transactions on Pattern Analysis and Machine Intelligence
Significant edges in the case of non-stationary Gaussian noise
Pattern Recognition
Trajectory fusion for three-dimensional volume reconstruction
Computer Vision and Image Understanding
Fast polynomial segmentation of digitized curves
DGCI'06 Proceedings of the 13th international conference on Discrete Geometry for Computer Imagery
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The detailed structure of intensities in the local neighborhood of an edge can often indicate the nature of the physical event givinig rise to that edge. We argue that the limit, as we approach arbitrarily close to either side of an edge, of such image parameters as type of texture, texture gradient, color, appropriate directional derivatives of intensity, etc., is a key aspect of this structure. However, the general problem of capturing this local structure is surprisingly complex. Thus, we restrict ourselves in this paper to a relatively simple domain驴one-dimensional cuts through idealized images modeled by piecewise smooth (C1) functions corrupted by Gaussian noise. Within this domain, we define local structure to be the limit of the uncorrupted intensity and of its derivatives as we approach arbitrarily close to either side of a discontinuity. We develop a technique that captures this local structure while simultaneously locating the discontinuities, and demonstrate that these tasks are in fact inseparable. The technique is an extension, using estimation theory, of the classical definition of discontinuity. It handles, in a consistent fashion, both jump discontinuities in the function and jump discontinuities in its first derivative (so-called step-edges are a special case of the former and roof-edges of the latter). It also integrates, again in a consistent fashion, information derived from a number of different neighborhood sizes.