Noise Reduction Using Wiener Filter Method

This MATLAB program implements noise reduction using the Wiener filter method, which outperforms spectral subtraction by avoiding sharp residual noise artifacts. Wiener filtering is a classical signal processing technique that effectively removes noise components from signals, resulting in cleaner and more interpretable outputs. The program processes input signals through Wiener filter implementation, which involves estimating signal and noise power spectra to compute optimal frequency-domain filter coefficients. Key implementation aspects include: - Calculating signal statistics and noise characteristics - Applying frequency-domain filtering with adaptive weights - Preserving signal integrity while suppressing noise components Unlike spectral subtraction, which often suffers from musical noise due to abrupt spectral transitions, Wiener filtering provides smoother noise suppression by incorporating statistical signal properties. The method excels particularly for signals without dominant sharp noise components, making it preferable for applications requiring balanced noise reduction and signal preservation. The algorithm minimizes mean square error between the original and estimated signals, ensuring optimal performance under Gaussian noise assumptions.