On the quick convergence of PSF estimation for single image blind deblurring
Muhammad Hasnain Waleed, Aftab Khan, Ashfaq Khan · 2017
This research work investigates various search optimization algorithms for quick estimation of blurring filter for single image blind deblurring. The optimization algorithms include Genetic Algorithm (GA), Ant Colony Optimization (ACO) and Particle Swarm Optimization (PSO). Validation has been performed on various image and multiple image quality metrics were utilized for the analysis of convergence of these algorithms in digital image restoration. Wiener filter was used as the deblurring filter of choice as it is non-iterative and aids in noise suppression. The PSO based image deblurring scheme converges relatively faster and requires fewer parameters to adjust as compared to the GA and ACO.