MATLAB Programming Code for Image Motion Deblurring

This project involves developing MATLAB code to remove motion blur from images. Motion blur is a common image degradation effect that captures the trajectory of moving objects in photographs. Implementing motion deblurring through programming can significantly enhance image clarity and quality. In MATLAB, this can be achieved using various image processing functions and algorithms. Key implementation approaches include: - Convolution operations with carefully designed point spread functions (PSF) to model and reverse blur effects - Frequency domain filtering techniques using Fourier transforms and Wiener filtering for noise-robust deconvolution - Motion vector estimation algorithms to determine blur direction and length parameters - Regularized optimization methods like Richardson-Lucy deconvolution for handling noise and artifacts The implementation typically involves functions such as fft2/ifft2 for Fourier analysis, deconvwnr for Wiener filtering, and deconvlucy for iterative restoration. Programming motion deblurring presents an engaging challenge that deepens understanding of fundamental concepts in image processing and computer vision, particularly in the areas of inverse problems, regularization techniques, and optical system modeling.