A model-based approach to shape from focus

Shape from focus (SFF) estimates the structure of a 3D object using the degree of focus as a cue in a sequence of observations. The estimate of the depth profile is however, vulnerable to lack of sufficient scene texture. In this paper, we propose a method to improve the estimate of the structure of the object by exploiting neighbourhood dependencies. A degradation model is used to describe the formation of space-variantly blurred observations in SFF. The shape of the object is modeled as a Markov random field and a suitably derived objective function is minimized to arrive at the final estimate of the shape.