Wiener Restoration: MATLAB Implementation for Grayscale Images

In this documentation, we demonstrate how to implement Wiener filtering for grayscale images using MATLAB. Wiener filtering is a powerful technique widely used in image processing and restoration, effectively removing noise and distortions while enhancing image clarity and quality. This guide provides a comprehensive overview of Wiener filtering principles and step-by-step implementation procedures, including how to read and load image files, apply the Wiener filtering algorithm, and adjust filter parameters for optimal results. The implementation utilizes key MATLAB functions such as imread() for image input, wiener2() for two-dimensional adaptive noise filtering, and imshow() for result visualization. We include practical code examples demonstrating noise estimation techniques and parameter optimization approaches, along with visual demonstrations to facilitate better understanding and application of this technique. Through this tutorial, you will master Wiener filtering implementation for grayscale images in MATLAB, providing valuable guidance for your future image processing projects.