Images contain information about the spatial properties of the scene they depict. When coupled with suitable assumptions, images can be used to infer three-dimensional information. This useful volume concentrates on motion blur and defocus, which can be exploited to infer the 3-D structure of a scene -- as well as its radiance properties -- and which in turn can be used to generate novel images with better quality. The book presents a coherent analytical framework for the analysis and design of algorithms to estimate 3-D shape from defocused and motion blurred images, and to eliminate defocus and motion blur to yield restored images. It further provides a collection of algorithms that are optimal with respect to the chosen model and estimation criterion.