Denoising point sets via L0L0 minimization

We present an anisotropic point cloud denoising method using L0L0 minimization. The L0L0 norm directly measures the sparsity of a solution, and we observe that many common objects can be defined as piecewise smooth surfaces with a small number of features. Hence, we demonstrate how to apply an L0L0 optimization directly to point clouds, which produces sparser solutions and sharper surfaces than either the L1L1 or L2L2 norm. Our method can faithfully recover sharp features while at the same time smoothing the remaining regions even in the presence of large amounts of noise.