Roughness Estimation and Image Rendering for Glossy Object Surface

We study the relationship between the physical surface roughness of the glossy surfaces of dielectric objects and the roughness parameter in image rendering. The former refers to a measure of the microscopic surface structure of a real object's surface. The latter is a model parameter used to produce the realistic appearance of objects. The target dielectric objects to analyze the surface roughness are handcrafted lacquer plates with controlled surface glossiness, as well as several plastics and lacquer products from everyday life. We first define the physical surface roughness as the standard deviation of the surface normal, and provide the computational procedure. We use a laser scanning system to obtain the precise surface height information at tiny flat areas of a surface. Next, a method is developed for estimating the surface roughness parameter based on images taken of the surface with a camera. With a simple setup for observing a glossy flat surface, we estimate the roughness parameter by fitting the Beckmann function to the image intensity distribution in the observed HDR image using the least squares method. A linear relationship is then found between the measurement-based surface roughness and image-based surface roughness. We present applications to glossy objects with curved surfaces.