A method is presented for recovering reflectance parameters of optically rough surfaces from a range and a brightness image, both of which are generated by a range-finder. The reflectance model of an optically rough surface consists of two components, known as Lambertian and specular components and respectively represented as a cosine and a Gaussian function, and contains the following three basic parameters: the Lambertian strength, specular strength, and specular sharpness. An iterative least-squares fitting method is used to obtain these parameters derived from range and brightness images. Assuming all pixels only contain the Lambertian component, the authors fit the Lambertian function to all the data points. Based on the fitting of these results, they use a threshold derived from a sensor model of the range-finder and exclude those pixels lying outside the bounds of this threshold. To examine the convergence of the algorithm, the authors implemented this algorithm and applied it to several synthesized images. Several experiments using real images demonstrated the applicability of the algorithm.
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