TY - GEN
T1 - A volume-based method for denoising on curved surfaces
AU - Biddle, Harry
AU - von Glehn, Ingrid
AU - Macdonald, Colin B.
AU - Marz, Thomas
N1 - KAUST Repository Item: Exported on 2020-10-01
Acknowledged KAUST grant number(s): KUK-C1-013-04
Acknowledgements: The work of all authors was partially supported by Award No KUK-C1-013-04 made by King Abdullah University of Science and Technology(KAUST).
This publication acknowledges KAUST support, but has no KAUST affiliated authors.
PY - 2013/9
Y1 - 2013/9
N2 - 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.
AB - 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.
UR - http://hdl.handle.net/10754/597437
UR - http://ieeexplore.ieee.org/document/6738109/
UR - http://www.scopus.com/inward/record.url?scp=84897713728&partnerID=8YFLogxK
U2 - 10.1109/ICIP.2013.6738109
DO - 10.1109/ICIP.2013.6738109
M3 - Conference contribution
SN - 9781479923410
SP - 529
EP - 533
BT - 2013 IEEE International Conference on Image Processing
PB - Institute of Electrical and Electronics Engineers (IEEE)
ER -