MATLAB Source Code for Iterative Blind Deconvolution Algorithm in Digital Image Processing for Image Deblurring

This document discusses image deblurring and iterative blind deconvolution algorithms in digital image processing. These algorithms are designed to process blurred images, making them clear and recognizable. Through their implementation, we can enhance image quality and restore details that have been distorted due to blurring. The MATLAB implementation specifically utilizes key functions such as fft2() for Fourier transforms and deconvblind() for blind deconvolution operations. The algorithm iteratively estimates both the point spread function (PSF) and the original sharp image through optimization techniques like maximum likelihood estimation. For practical implementation, the MATLAB code includes noise regularization parameters and convergence criteria to handle real-world image degradation scenarios. The iterative process typically involves alternating between PSF estimation and image restoration until satisfactory results are achieved. If you are interested in digital image processing and image deblurring algorithms, this document provides detailed information about iterative blind deconvolution along with practical MATLAB source code examples that can be executed and tested to verify their effectiveness and accuracy.