Imaging in multiplexed illumination

Lighting plays an important role in many applications of computer vision, machine vision and computer graphics. Often, an object needs to be photographed multiple times, in each of which lighting comes from a different direction. Lighting which uses a single source per image is prone to dynamic range problems, especially in dark areas and in specular highlights. In addition, it becomes a practical problem to use an increasingly larger number of discrete sources (say, hundreds). To counter these problems we develop a novel illumination strategy. In each image, multiple light sources irradiate the scene simultaneously. The set of light sources is different in each image, but not mutually exclusive. Then, the contribution of each individual source is extracted in computational post-processing. The number of acquired images using this approach is the same as the number used in single-source images. However, thanks to the multiplexing of light in the raw images, more light is used from a variety of directions, diminishing problems of dynamic range. We derive the optimal illumination multiplexing scheme, which increases the SNR of the images by (√n}/2, where {n} is the number of sources. This lighting strategy is complemented by a novel illumination setup. The setup is easily built and scaled to a huge number of sources, and is controllable by the computer. These advantages are obtained since the apparatus is based on indirect lighting originating from an LCD projector.

[1]  N. Sloane,et al.  Hadamard transform optics , 1979 .

[2]  Kristin J. Dana,et al.  Device for convenient measurement of spatially varying bidirectional reflectance. , 2004, Journal of the Optical Society of America. A, Optics, image science, and vision.

[3]  David J. Kriegman,et al.  Image-based modeling and rendering of surfaces with arbitrary BRDFs , 2001, Proceedings of the 2001 IEEE Computer Society Conference on Computer Vision and Pattern Recognition. CVPR 2001.

[4]  Shree K. Nayar,et al.  Lighting sensitive display , 2004, ACM Trans. Graph..

[5]  David J. Kriegman,et al.  From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose , 2001, IEEE Trans. Pattern Anal. Mach. Intell..

[6]  Stephen H. Westin,et al.  Image-based bidirectional reflectance distribution function measurement. , 2000, Applied optics.

[7]  Ronen Basri,et al.  Lambertian Reflectance and Linear Subspaces , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[8]  Terence Sim,et al.  The CMU Pose, Illumination, and Expression Database , 2003, IEEE Trans. Pattern Anal. Mach. Intell..

[9]  Shree K. Nayar,et al.  A theory of multiplexed illumination , 2003, Proceedings Ninth IEEE International Conference on Computer Vision.

[10]  Paul E. Debevec,et al.  Image-based lighting , 2002, IEEE Computer Graphics and Applications.