Back to Basics: Fast Denoising Iterative Algorithm

arXiv:2311.06634v2 Announce Type: replace-cross
Abstract: We introduce Back to Basics (BTB), a fast iterative algorithm for noise reduction. Our method is computationally efficient, does not require training or ground truth data, and can be applied in the presence of independent noise, as well as correlated (coherent) noise, where the noise level is unknown. We examine three study cases: natural image denoising in the presence of additive white Gaussian noise, Poisson-distributed image denoising, and speckle suppression in optical coherence tomography (OCT). …

abstract algorithm arxiv basics cs.cv data denoising eess.iv independent iterative noise training truth type