Blind restoration of images blurred by complex camera motion and simultaneous recovery of 3D scene structure

Abstract

We present an algorithm that uses two or more images of the same scene blurred by camera motion for recovery of 3D scene structure and simultaneous restoration of sharp image. Motion blur is modeled by convolution with space-varying mask that changes its scale with the distance of imaged objects. The mask can be of arbitrary shape corresponding to the integral of the camera path during the pick-up time, which can be measured for instance by inertial sensors. This approach is more general than previously published algorithms that assumed shift-invariant blur or fixed, rectangular or Gaussian, mask shape. Algorithm can be easily parallelized and has a potential to be used in practical applications such as compensation of camera shake during long exposures