Abstract
This paper addresses the problem of feature enhancement in noisy images when the feature is known to be constrained to a manifold. As an example, we study the problem of direction denoising. This problem was treated recently and several solutions were proposed. The various solutions share the same structure. They are composed of two terms: A difusion term and a projection term. Analytically, the solutions differ in the difusion part. The projection part is equivalent in all works. Yet, as it is often the case, the analytically equivalent projection terms differ from a numerical viewpoint. We present in this work a new parameterization of the problem that enables us to work always in a numerically stable way.
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© 2001 Springer-Verlag Berlin Heidelberg
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Sochen, N.A., Kimmel, R. (2001). Combing a Porcupine via Stereographic Direction Difusion. In: Kerckhove, M. (eds) Scale-Space and Morphology in Computer Vision. Scale-Space 2001. Lecture Notes in Computer Science 2106, vol 2106. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-47778-0_28
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DOI: https://doi.org/10.1007/3-540-47778-0_28
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