Denoising: from classical methods to deep CNNs

arXiv:2404.16617v1 Announce Type: new
Abstract: This paper aims to explore the evolution of image denoising in a pedagological way. We briefly review classical methods such as Fourier analysis and wavelet bases, highlighting the challenges they faced until the emergence of neural networks, notably the U-Net, in the 2010s. The remarkable performance of these networks has been demonstrated in studies such as Kadkhodaie et al. (2024). They exhibit adaptability to various image types, including those with fixed regularity, facial images, and …

abstract analysis arxiv challenges cnns cs.cv denoising emergence evolution explore fourier highlighting image math.ho networks neural networks paper performance review type wavelet