Gaussian Noise Removal from Digital Image Using the Iterative MMSE Filter

The aim of this paper is to conduct extensive research on grayscale images using an iterative MMSE algorithm and add-on white Gaussian noise (AWGN). Using varying window sizes and iteration values, we aim to obtain optimal parameters that will provide the best signal-to-noise ratio (SNR) and Structural Similarity Index Measure (SSIM) values possible. In quantitative terms, the research demonstrates the value of choosing the appropriate size windows and the number of iterations used in the filtering process.