ESTIMATING MOTION BLUR PARAMETERS BY PARTICLE SWARM OPTIMIZATION METHOD

When the parameters of motion blur are known, the Wiener filter proves to be an effective tool for restoring degraded images. This paper introduces an optimization problem aimed at estimating the suitable parameters for motion blur. To tackle this problem, a particle swarm optimization algorithm is utilized. Extensive experiments conducted on the GoPro dataset showcase the superior performance of the proposed framework compared to other state-of-the-art techniques for image motion deblurring.