Alternating Optimizations - Computational Performance - Joint Bilateral Up Samplings - L0 Norm - Mesh Denoising - Nonconvex Optimization - Sparse Regularizations - State-of-the-Art Methods

Alternating Optimizations - Computational Performance - Joint Bilateral Up Samplings - L0 Norm - Mesh Denoising - Nonconvex Optimization - Sparse Regularizations - State-of-the-Art Methods

Robust and Effective Mesh Denoising Using $<$mml:Math Xmlns:Mml=\"http://www.w3.org/1998/Math/MathML\" Id=\"mml51\" Display=\"inline\" Overflow=\"scroll\" Altimg=\"si1.Gif\"$><$mml:Msub$><$mml:Mrow$><$mml:mi$>$L$<$/Mml:Mi$><$/Mml:Mrow$><$mml:Mrow$><$mml:Mn$>$0$<$/Mml:Mn$><$/Mml:Mrow$><$/Mml:Msub$><$/Mml:Math$>$ Sparse Regularization

Mesh denoising is of great practical importance in geometric analysis and processing. In this paper we develop a novel L0sparse regularization method to robustly and reliably …

yong-zhao
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