Estimating surface reflectance properties from images under unknown illumination

Ron O. Dror; Edward H. Adelson; Alan S. Willsky

doi:10.1117/12.429494

8 June 2001 Estimating surface reflectance properties from images under unknown illumination

Ron O. Dror, Edward H. Adelson, Alan S. Willsky

Proceedings Volume 4299, Human Vision and Electronic Imaging VI; (2001) https://doi.org/10.1117/12.429494
Event: Photonics West 2001 - Electronic Imaging, 2001, San Jose, CA, United States

Abstract

Physical surfaces such as metal, plastic, and paper possess different optical qualities that lead to different characteristics in images. We have found that humans can effectively estimate certain surface reflectance properties from a single image without knowledge of illumination. We develop a machine vision system to perform similar reflectance estimation tasks automatically. The problem of estimating reflectance form single images under unknown, complex illumination proves highly under-constrained due to the variety of potential reflectances and illuminations. Our solution relies on statistical regularities in the spatial structure of real-world illumination. These regularities translate into predictable relationships between surface reflectance and certain statistical features of the image. We determine these relationships using machine learning techniques. Our algorithms do not depend on color or polarization; they apply even to monochromatic imagery. An ability to estimate reflectance under uncontrolled illumination will further efforts to recognize materials and surface properties, tp capture computer graphics models from photographs, and to generalize classical motion and stereo algorithms such that they can handle non-Lambertian surfaces.

Citation Download Citation

Ron O. Dror, Edward H. Adelson, and Alan S. Willsky "Estimating surface reflectance properties from images under unknown illumination", Proc. SPIE 4299, Human Vision and Electronic Imaging VI, (8 June 2001); https://doi.org/10.1117/12.429494

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