Wiener filter python code github

1. How does a Wiener filter work?
2. Why Wiener filter is used?
3. What is the difference between inverse filter and Wiener filter?

How does a Wiener filter work?

The goal of the Wiener filter is to compute a statistical estimate of an unknown signal using a related signal as an input and filtering that known signal to produce the estimate as an output. For example, the known signal might consist of an unknown signal of interest that has been corrupted by additive noise.

Why Wiener filter is used?

It removes the additive noise and inverts the blurring simultaneously. The Wiener filtering is optimal in terms of the mean square error. In other words, it minimizes the overall mean square error in the process of inverse filtering and noise smoothing. The Wiener filtering is a linear estimation of the original image.

What is the difference between inverse filter and Wiener filter?

However, inverse filtering is very sensitive to additive noise. The Wiener filtering executes an optimal tradeoff between inverse filtering and noise smoothing. It removes the additive noise and inverts the blurring simultaneously.