Image Denoising Implementation Using MATLAB with Wiener Filter Algorithm

This article presents an image denoising program implemented in MATLAB using the Wiener filter method. The program effectively removes noise from images to enhance clarity and visual quality. We have included sample images within the program package, allowing users to immediately execute and test the functionality. The Wiener filter approach represents a widely-adopted image processing technique that employs statistical modeling of noise characteristics to achieve noise reduction. In our implementation, the core algorithm involves estimating the power spectra of both the original image and noise components, followed by applying frequency-domain filtering using MATLAB's built-in wiener2 function for grayscale images or custom implementations for color images. The program demonstrates practical applications of signal processing theory through adaptive filtering that adjusts based on local image statistics, effectively preserving edges while suppressing noise patterns. Key MATLAB functions utilized include image read/write operations (imread/imwrite), noise estimation routines, and frequency-domain transformation tools (fft2/ifft2) when implementing custom Wiener filter versions beyond the basic wiener2 function.