Abstract
This paper describes the complete implementation of a blind image denoising algorithm, that takes any digital image as input. In a first step the algorithm estimates a Signal and Frequency Dependent (SFD) noise model. In a second step, the image is denoised by a multiscale adap- tation of the Non-local Bayes denoising method. We focus here on a careful analysis of the denoising step and present a detailed discussion of the influence of its parameters. Extensive commented tests of the blind denoising algorithm are presented, on real JPEG images and on scans of old photographs.
Cite
CITATION STYLE
Lebrun, M., Colom, M., & Morel, J.-M. (2015). The Noise Clinic: a Blind Image Denoising Algorithm. Image Processing On Line, 5, 1–54. https://doi.org/10.5201/ipol.2015.125
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.