The Wiener filter Global iterative approaches Local filters use information from a local neighborhood to restore pixels one at a time. In contrast, global filters use information from the entire image to restore each pixel. To achieve this, there must be a mechanism for information to travel between every pair of pixels. Wiener filters achieve this by using the frequency domain representation of the image, in which each Fourier coefficient is affected by the value of almost every pixel.
Many iterations allow information to propagate globally.
A shortcoming of global iterative approaches is that they tend to be quite slow. Some of the algorithms which generate impressive results require hours to filter a single image. For this reason, parallel implementations of these algorithms have been explored. Most of the algorithms are quite complicated, which makes comparison with them difficult. Implementing some of the newer approaches would be a worthy thesis on its own.