I am reading the paper A Bias-Variance Approach for the Nonlocal Means.
One sentence from the paper is as follow:
To discuss the tuning of parameters of the NLM, we interpret this choice as a bias-variance dilemma.
I encountered bias-variance for the first time in papers on image denoising and I'm not sure about the meaning of bias-variance.
Does the bias mean the difference between the original image and denoised image?
What does variance mean? Does it mean some measurement about the denoised image?
What I guess is:
For the original image, the bias is smallest and the variance is largest.
For the denoised image with every pixel having pixel value of mean of the original image, the bias is largest and the variance is smallest.
How can this guide to design de-noising method or tuning parameters?