On the relative brightness of specular and diffuse reflection

Inhomogeneous dielectric surfaces exhibit both diffuse and specular reflection components. While various reflection models have been proposed for both of these components, the prediction of the relative strengths of these components in computer vision and computer graphics has so far not had a strong physical motivation. We propose in this paper a reflectance model for combined diffuse and specular reflection from dielectric materials which involves purely physical parameters (i.e., no ad hoc weighting of specular and diffuse components). This reflectance model is used to predict the relative strength of diffuse and specular reflection components in terms of imaging geometry, dielectric surface parameters, and, solid angular extent of incident light. We derive lower bounds on the contrast ratio between a specularity and surrounding diffuse reflecting regions. These can be used effectively to rule out highly contrasting diffuse reflecting regions being misidentified as specularities under a number of conditions which can significantly aid intensity-based specularity detection methods, and in turn image understanding. The theoretical developments in this paper can be used to predict the photometric dynamic range of illuminated objects which can be essential to inspection methods in machine vision. The developments in this paper can also be used in computer graphics for the physically precise rendering of the relative strengths of specular and diffuse reflection from inhomogeneous dielectrics.<<ETX>>

[1]  J P Frisby,et al.  PMF: A Stereo Correspondence Algorithm Using a Disparity Gradient Limit , 1985, Perception.

[2]  K. Torrance,et al.  Theory for off-specular reflection from roughened surfaces , 1967 .

[3]  David B. Cooper,et al.  Bayesian Recognition of Local 3-D Shape by Approximating Image Intensity Functions with Quadric Polynomials , 1984, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Chia-Hoang Lee,et al.  Using highlights to constrain object size and location , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[5]  Katsushi Ikeuchi,et al.  Extracting the shape and roughness of specular lobe objects using four light photometric stereo , 1991, Proceedings 1992 IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[6]  Lawrence B. Wolff Diffuse reflectance model for dielectric surfaces , 1993, Other Conferences.

[7]  B K Horn,et al.  Calculating the reflectance map. , 1979, Applied optics.

[8]  Steven A. Shafer,et al.  Using color to separate reflection components , 1985 .

[9]  Lawrence B. Wolff,et al.  Using polarization to separate reflection components , 1989, Proceedings CVPR '89: IEEE Computer Society Conference on Computer Vision and Pattern Recognition.

[10]  Azriel Rosenfeld,et al.  Determining plane orientation from specular reflectance , 1985, Pattern Recognit..

[11]  Andrew Blake,et al.  Geometry From Specularities , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[12]  Andrew Blake,et al.  Specular Stereo , 1985, IJCAI.

[13]  Donald P. Greenberg,et al.  A comprehensive physical model for light reflection , 1991, SIGGRAPH.

[14]  Gavin J. Brelstaff,et al.  Inferring surface shape from specular reflections , 1988 .

[15]  Kosuke Sato,et al.  Determining reflectance parameters using range and brightness images , 1990, [1990] Proceedings Third International Conference on Computer Vision.

[16]  Andrew Blake,et al.  Detecting Specular Reflections Using Lambertian Constraints , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[17]  Robert L Cook,et al.  A reflectance model for computer graphics , 1981, SIGGRAPH '81.

[18]  Lawrence B. Wolff,et al.  Relative brightness of specular and diffuse reflection , 1994 .

[19]  Thomas O. Binford,et al.  Local shape from specularity , 1988, Comput. Vis. Graph. Image Process..

[20]  L. B. Wolff Diffuse-reflectance model for smooth dielectric surfaces , 1994 .

[21]  T. Kanade,et al.  USING A COLOR REFLECTION MODEL TO SEPARATE HIGHLIGHTS FROM OBJECT COLOR , 1987 .