Generalized S-Transform Based Fractal Image Denoising Processing Method

This presents a fractal image denoising processing method based on the generalized S-transform, implemented using MATLAB. The approach employs time-frequency analysis techniques where the generalized S-transform provides adaptive windowing capability for better noise separation. The implementation includes key functions for signal decomposition, threshold filtering in the transform domain, and signal reconstruction. The method effectively enhances image quality by removing noise interference, resulting in clearer images with improved detail preservation. The generalized S-transform serves as a powerful signal processing tool applicable across multiple domains including image processing, audio analysis, and biomedical signal processing. Through parameter optimization in the MATLAB code, users can adjust window functions and threshold parameters to achieve optimal denoising performance. The algorithm's modular structure allows for easy customization and performance enhancement. This implementation aims to support various image processing requirements with its flexible and efficient denoising capabilities.