Image deblurring through static or time-varying random perturbation medium

In a large plurality of applications, imaging quality is significantly reduced due to existence of static or time-varying random perturbation media. An example of such a medium can be a diffusive window through which we wish to image an object located behind, and not in proximity to, the window. Another example can be localized flow of turbulence (above hot surfaces such as black roads) or of aerosols distorting the imaging resolution of objects positioned behind the perturbation. We present a new deblurring approach for obtaining highly resolved imaging of objects positioned behind static or time-varying random perturbation media. The proposed approach for extraction of the high spatial frequencies is based on iterative computation similar to the well-known Gerchberg- Saxton algorithm for phase retrieval. By focusing our camera onto three planes positioned between the imaging camera and the perturbation, we are able to retrieve the phase distribution of those planes and then reconstruct the intensity of the object by numerical free space propagation of this extracted complex field to the estimated position of the object.