Estimation techniques of the background and detailed portion of an object in image superresolution

The extent of bandwidth extrapolation obtainable in a superresolution algorithm depends on the spatial extent of the object. However, in most of the problems encountered in real-world applications, the object is not spatially limited. To circumvent this problem, one can decompose the estimation problem into estimating the smooth background and then incorporating this knowledge to estimate the `sparsely distributed' detailed portion of the object. For example, in astronomical applications, the low photon count background is estimated initially, followed by the binary stars embedded in the background. In this paper we propose an iterative method to implement the two-step estimation technique. Further, we propose a modified version of the Richardson/Lucy algorithm to incorporate this two-step estimation. Some preliminary results on one-dimensional objects for the proposed algorithms are included.