What Are Intuitive Explanations for Shrinkage in the Context of Image Denoising?
In the image processing field shrinkage means we reduce the power of some components of the signal.
The idea is to have a basis which the signal can represented in in a sparse manner.
For instance, if the signal is harmonic, efficient basis would be the Fourier.
So if we look at harmonic signals and noise in Fourier we expect to see dominant component and other components are the noise, which will be shrinked in order to apply Denoising.
This is the idea behind what's known as Sparse Representations.
In the context of Image Denoising you may have a look at Image Denoising with Shrinkage and Redundant Representations.
In the general context you may have a look at the course Sparse Representations in Signal and Image Processing: Fundamentals.