MATLAB Implementation of Wiener Filter Restoration with Additional Image Restoration Algorithms

This document discusses several image restoration methods implemented in MATLAB, including Wiener filter restoration, regularized filter restoration, Lucy-Richardson restoration examples, blind deconvolution restoration, and inverse filter restoration algorithms. These techniques are designed to recover image details and enhance clarity, thereby improving overall image quality through sophisticated mathematical implementations.

Key implementation aspects include: Wiener filter restoration using MATLAB's deconvwnr function which minimizes mean square error; Regularized filtering through deconvreg function with constraint optimization; Lucy-Richardson algorithm implementation via deconvlucy employing iterative maximum likelihood estimation; Blind deconvolution using deconvblind for point spread function estimation; Inverse filtering approach handling frequency domain restoration with careful noise consideration. Each method addresses specific degradation models and requires appropriate parameter tuning for optimal results.