Unscented blind image de-blurring using camera with inertial measurement unit

Image blur resulting from camera motion is an annoying factor for robotic vision, especially for high-speed applications. This work proposes a sensor fusion model for blind image de-blurring using inertial measurement unit. The model attempts to observe the camera motion, estimate the point spread function and de-convolute the image simultaneously. To solve the problem, an iterative estimation procedure using Maximum A-Posteriori Expectation-Maximization (MAP-EM) algorithms and Unscented Kalman Filter are proposed. Simulation results show the feasibility of the proposed formulation to blindly de-blurring the image under camera motion.