MATLAB Code Implementation of Wiener Filter for Signal and Image Processing

This MATLAB M-file implements Wiener filtering, a widely used algorithm for signal and image processing applications. The implementation includes two practical use cases demonstrating real-world applications with complete code examples. Wiener filtering is a fundamental signal processing technique that enhances signal quality and reliability through sophisticated filtering and noise reduction mechanisms. In image processing, Wiener filtering is extensively applied for image denoising and enhancement tasks. The MATLAB implementation provides a complete framework for executing Wiener filter algorithms, featuring two fully coded application scenarios for learning and reference purposes. The first application demonstrates signal processing implementation, showcasing how Wiener filtering extracts meaningful information from signals while effectively suppressing noise and interference. Through frequency-domain filtering implementation using MATLAB's fft and ifft functions, users can achieve cleaner and more accurate signal results, facilitating improved downstream analysis and processing. The code includes practical examples of handling additive white Gaussian noise (AWG) scenarios. The second application focuses on image processing implementation, illustrating Wiener filtering's capability for image denoising and enhancement. Digital images often contain various noise patterns and distortions that compromise image quality and detail resolution. The implementation employs 2D Wiener filtering algorithms with adaptive noise variance estimation, effectively reducing noise while enhancing image clarity and detail preservation. The code demonstrates practical techniques for handling common image artifacts through spatial domain filtering approaches. This comprehensive MATLAB Wiener filter implementation serves as a valuable tool for both signal and image processing tasks, providing two fully functional application examples with detailed code commentary. Wiener filtering plays a critical role in both academic research and practical applications, enabling significant improvements in signal and image quality for enhanced data interpretation and analysis across various domains. The implementation includes essential MATLAB functions such as wiener2 for image processing and custom frequency-domain implementations for signal processing scenarios.