Accelerated non-linear denoising filters

Self-guided denoising filters, such as bilateral, guided, and total variation filters, may require multiple evaluations if noise is large and filter parameters are tuned to preserve sharp edges. We formulate three acceleration techniques of the resulted iterations: conjugate gradient, Nesterov, and heavy ball methods. We numerically compare these techniques for image denoising and demonstrate 5-13 times speed-up.