Robles-Kelly, A.Hancock, E.R.Peter Hall and Philip Willis2016-02-092016-02-0920033-905673-54-1https://doi.org/10.2312/vvg.20031029This paper describes a method for performing Lambertian reflectance for rough and specular surfaces. Rather than using an existing reflectance model, we present a method for estimating the reflectance function from image data. The method makes use of the Gauss map between a surface and a unit sphere. Under conditions in which the light source direction and the viewer direction are identical, we show how the reflectance function can be represented by a polar function on the unit sphere. We pose the problem of recovering the reflectance function as that of estimating a tabular representation of the polar function. A simple analysis shows how the tabular representation of the reflectance function can be obtained using the accumulative distribution of image gradients. By modifying the reflectance function and back-projecting, we can render the surface with alternative lighting models. Here, we choose to back-project a Lambertian reflectance model. This allows us to be remove specularities from shiny surfaces and compensate from boundary ''flattening'' for rough surfaces. We illustrate the utility of the method on a variety of real world imagery.I.4.8 [Image Processing and Computer Vision]Lambertian correctionBRDF approximation10.2312/vvg.20031029A. Robles-Kelly and E.R. Hancock-I.4.8 [Image Processing and Computer Vision]: Lambertian correction, BRDF approximation