Image intrinsic values from shading information

Since the pioneer work of Horn, a considerable amount of computer vision research has been done on shape from shading (SFS). The basic idea of SFS is to infer the shape of an object from its shading information in a single image. Since this problem is ill-posed, a number of assumptions have been used extensively in the computer vision community for the SFS problem, such as orthographic projection, Lambertian reflectance model, single light source, and constant surface albedo. In this paper, starting with this typical set of assumptions, we derive new image intrinsic values based on image shading information. We derive these values for a number of reflectance models such as the linear and quadratic models in addition to the popular Lambertian model. We validated the obtained intrinsic values on hundreds of real and synthetic images.