A weight matrix based blind Super Resolution restoration algorithm

Approximate description of the observation model has severely prevented performance improvement of the existing super resolution (SR) algorithms. To solve this problem, a new weight-matrix based blind super resolution algorithm is proposed in this paper. A new observation model based on a motion compensate matrix and a weight-matrix is defined first. Then it is introduced into the traditional framework of maximum a posterior (MAP), where the problem of super resolution is converted to joint estimation of the weight matrix and the high resolution (HR) image. Evaluated by both still and active image sequences, the proposed algorithm can model the degrading process of the acquired low resolution images accurately. It shows obvious performance improvement compared with the traditional MAP based super resolution algorithm. For several cases, it has even exceeded the results when the observation model is known.