Fixed-Point Iteration Method for Image Denoising Development

This paper presents a MATLAB implementation of a fixed-point iteration method for image denoising based on partial differential equations. The algorithm begins with preprocessing the input image, followed by applying fixed-point iteration to reduce noise. The implementation involves iterative computations on image pixels through matrix operations and convolution functions, gradually minimizing noise impact to produce clearer images. Key MATLAB functions like imfilter and iterative solvers were employed for pixel-level processing. Additional techniques were integrated to enhance algorithm performance, including adaptive parameter adjustment using statistical measures of local image regions and multi-scale processing through pyramid decomposition. These improvements successfully boosted the denoising effectiveness, making the algorithm more adaptable to various image types. Future research will focus on algorithm optimization through parallel computing implementation and exploration of other image processing techniques like deep learning integration.