Random matrix route to image denoising

Understand

We make use of recent results from random matrix theory to identify a derived threshold, for isolating noise from image features.

• The procedure assumes the existence of a set of noisy images, where denoising can be carried out on individual rows or columns independently.
• The fact that these are guaranteed to be correlated makes the correlation matrix an ideal tool for isolating noise.
• The random matrix result provides lowest and highest eigenvalues for the Gaussian random noise for which case, the eigenvalue distribution function is analytically known.