Image denoising via patch based L1-norm principal component analysis

Patch-based image denoising approaches have gained popularity recently. We propose an image denoising approach using subspaces that are fit using an L1-norm criterion. This new approach is competitive with existing approaches in terms of objective error metrics and visual fidelity, and has the added benefit that it can be implemented in parallel for large-scale applications.