A volume-based method for denoising on curved surfaces

Harry Biddle, Ingrid von Glehn, Colin B. Macdonald, Thomas Marz

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

We demonstrate a method for removing noise from images or other data on curved surfaces. Our approach relies on in-surface diffusion: we formulate both the Gaussian diffusion and Perona-Malik edge-preserving diffusion equations in a surface-intrinsic way. Using the Closest Point Method, a recent technique for solving partial differential equations (PDEs) on general surfaces, we obtain a very simple algorithm where we merely alternate a time step of the usual Gaussian diffusion (and similarly Perona-Malik) in a small 3D volume containing the surface with an interpolation step. The method uses a closest point function to represent the underlying surface and can treat very general surfaces. Experimental results include image filtering on smooth surfaces, open surfaces, and general triangulated surfaces. © 2013 IEEE.
Original languageEnglish (US)
Title of host publication2013 IEEE International Conference on Image Processing
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages529-533
Number of pages5
ISBN (Print)9781479923410
DOIs
StatePublished - Sep 2013
Externally publishedYes

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