Optical Splitting Trees for High-Precision Monocular Imaging

In this article, we consider the design of monocular multiview optical systems that form optical splitting trees, where the optical path topology takes the shape of a tree because of recursive beam splitting. Designing optical splitting trees is challenging when it requires many views with specific spectral properties. We introduce a manual design paradigm for optical splitting trees and a computer-assisted design tool to create efficient splitting-tree cameras. The tool accepts as input a specification for each view and a set of weights describing the user's relative affinity for efficiency, measurement accuracy, and economy. An optimizer then searches for a design that maximizes these weighted priorities. Our tool's output is a splitting-tree design that implements the input specification and an analysis of the efficiency of each root-to-leaf path. Automatically designed trees appear comparable to those designed by hand; we even show some cases where they are superior. With the help of the optimizer, the system demonstrates high dynamic range, focusing, matting, and hybrid imaging implemented on a single, reconfigurable camera containing eight sensors

[1]  Shree K. Nayar,et al.  High dynamic range imaging: spatially varying pixel exposures , 2000, Proceedings IEEE Conference on Computer Vision and Pattern Recognition. CVPR 2000 (Cat. No.PR00662).

[2]  References , 1971 .

[3]  Narendra Ahuja,et al.  Multiview panoramic cameras using mirror pyramids , 2004, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[4]  Narendra Ahuja,et al.  Split Aperture Imaging for High Dynamic Range , 2004, International Journal of Computer Vision.

[5]  Frédo Durand,et al.  Defocus video matting , 2005, SIGGRAPH 2005.

[6]  Jitendra Malik,et al.  Recovering high dynamic range radiance maps from photographs , 1997, SIGGRAPH '08.

[7]  Andrew Gardner,et al.  A lighting reproduction approach to live-action compositing , 2002, SIGGRAPH.

[8]  Murali Subbarao Parallel Depth Recovery By Changing Camera Parameters , 1988, [1988 Proceedings] Second International Conference on Computer Vision.

[9]  Shree K. Nayar,et al.  Assorted pixels: multi-sampled imaging with structural models , 2002, ECCV.

[10]  Steven A. Shafer,et al.  Depth from focusing and defocusing , 1993, Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.

[11]  Subhasis Chaudhuri,et al.  Depth From Defocus: A Real Aperture Imaging Approach , 1999, Springer New York.

[12]  Eiichiro Ikeda Image data processing apparatus for processing combined image signals in order to extend dynamic range , 1994 .

[13]  Shree K. Nayar,et al.  Real-time focus range sensor , 1995, Proceedings of IEEE International Conference on Computer Vision.

[14]  Marc Levoy,et al.  High-speed videography using a dense camera array , 2004, CVPR 2004.