Abstract
Computational photography combines plentiful computing, digital sensors, modern optics, actuators, and smart lights to escape the limitations of traditional cameras, enables novel imaging applications and simplifies many computer vision tasks. However, a majority of current Computational photography methods involves taking multiple sequential photos by changing scene parameters and fusing the photos to create a richer representation. Epsilon photography is concerned with synthesizing omnipictures and proceeds by multiple capture single image paradigm (MCSI).The goal of Coded computational photography is to modify the optics, illumination or sensors at the time of capture so that the scene properties are encoded in a single (or a few) photographs. We describe several applications of coding exposure, aperture, illumination and sensing and describe emerging techniques to recover scene parameters from coded photographs.
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References
Raskar, R., Tan, K., Feris, R., Yu, J., Turk, M.: Non-photorealistic Camera: Depth Edge Detection and Stylized Rendering Using a Multi-Flash Camera. In: Proc. ACM SIGGRAPH (2004)
Tumblin, J., Agrawal, A., Raskar, R.: Why I want a Gradient Camera. IEEE Computer Vision and Pattern Recognition (2005)
Raskar, R., Agrawal, A., Tumblin, J.: Coded exposure photography: motion deblurring using fluttered shutter. ACM Transactions on Graphics 25(3), 795–804 (2006)
Veeraraghavan, A., Raskar, R., Agrawal, A., Mohan, A., Tumblin, J.: Dappled Photography: Mask-Enhanced Cameras for Heterodyned Light Fields and Coded Aperture Refocusing. In: Proc. ACM SIGGRAPH (2007)
Nayar, S.K., Narasimhan, S.G.: Assorted Pixels: Multi-Sampled Imaging With Structural Models. In: Heyden, A., Sparr, G., Nielsen, M., Johansen, P. (eds.) ECCV 2002. LNCS, vol. 2353, pp. 636–652. Springer, Heidelberg (2002)
Debevec, M.: Recovering high dynamic range radiance maps from photographs. In: Proc. ACM SIGGRAPH (1997)
Mann, P.: Being ’undigital’ with digital cameras: Extending dynamic range by combining differently exposed pictures. In: Proc. Imaging Science and Technology 46th ann. conference (1995)
Morgan, M., Matusik, P., Hughes, D.: Defocus Video Matting. ACM Transactions on Graphics 24(3) (July 2005) (Proceedings of ACM SIGGRAPH 2005)
Adelson, E.H., Wang, J.Y.A.: Single Lens Stereo with a Plenoptic Camera. IEEE Transactions on Pattern Analysis and Machine Intelligence 14(2) (February 1992)
Ren, N.: Fourier Slice Photography. In: ACM SIGGRAPH (2005)
Morimura: Imaging method for a wide dynamic range and an imaging device for a wide dynamic range. U.S. Patent 5455621 (October 1993)
Levoy, M., Hanrahan, P.: Light field rendering. In: ACM SIGGRAPH, pp. 31–42 (1996)
Gortler, S.J., Grzeszczuk, R., Szeliski, R., Cohen, M.F.: The Lumigraph. In: ACM SIGGRAPH, pp. 43–54 (1996)
Dowski Jr., E.R., Cathey, W.T.: Extended depth of field through wave-front coding. Applied Optics 34(11), 1859–1866 (1995)
Georgiev, T., Zheng, C., Nayar, S., Salesin, D., Curless, B., Intwala, C.: Spatio-angular Resolution Trade-Offs in Integral Photography. In: Proceedings of Eurographics Symposium on Rendering (2006)
Tumblin, J.: Slides on the Photographic Signal and Film-like Photography. In: Course 3: Computational Photography, ACM SIGGRAPH (2005), www.merl.com/people/raskar/photo/Slides/01BasicJTJuly31.ppt
Light fields, http://en.wikipedia.org/wiki/Light_field
Bidirectional reflectance distribution function, http://en.wikipedia.org/wiki/BRDF
Synthetic Aperture Radar, http://en.wikipedia.org/wiki/Synthetic_aperture_radar
Programmable Interface Controller, http://en.wikipedia.org/wiki/PIC_microcontroller
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Raskar, R. (2009). Computational Photography: Epsilon to Coded Photography. In: Nielsen, F. (eds) Emerging Trends in Visual Computing. ETVC 2008. Lecture Notes in Computer Science, vol 5416. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-00826-9_10
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DOI: https://doi.org/10.1007/978-3-642-00826-9_10
Publisher Name: Springer, Berlin, Heidelberg
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