Smart Depth of Field Optimization Applied to a Robotised View Camera
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- 作者：Stéphane Mottelet (1) stephane.mottelet@utc.fr
Luc de Saint?Germain (2) lsg@lsg-studio.com
Olivier Mondin (2) - 关键词：Large format photography – Computational photography – Scheimpflug principle
- 刊名：Journal of Mathematical Imaging and Vision
- 出版年：2012
- 出版时间：September 2012
- 年：2012
- 卷：44
- 期：1
- 页码：1-18
- 全文大小：2.7 MB
- 参考文献：1. Bigler, E.: Depth of field and Scheimpflug rule: a minimalist geometrical approach. http://www.galerie-photo.com/profondeur-de-champ-scheimpflug-english.html (2002)
2. Evens, L.: View camera geometry. http://www.math.northwestern.edu/len/photos/pages/vc.pdf (2008)
3. Larmore, L.: Introduction to Photographic Principles. Dover, New York (1965)
4. Merklinger, A.: Focusing the View Camera. Bedford. http://www.trenholm.org/hmmerk/FVC161.pdf (1996)
5. Ray, S.F.: Applied Photographic Optics, 3rd edn. Focal Press, Waltham (2002)
6. Scheimpflug, T.: Improved method and apparatus for the systematic alteration or distortion of plane pictures and images by means of lenses and mirrors for photography and for other purposes. GB Patent No. 1196, 1904
7. Tillmans, U.: Creative Large Format: Basics and Applications. Sinar AG, Feuerthalen (1997)
8. Wheeler, R.: Notes on view camera geometry. http://www.bobwheeler.com/photo/ViewCam.pdf (2003) - 作者单位：1. Laboratoire de Mathématiques Appliquées, Université de Technologie de Compiègne, 60205 Compiègne, France2. Luxilon, 21, rue du Calvaire, 92210 Saint-Cloud, France
- 刊物类别：Computer Science
- 刊物主题：Computer Imaging, Vision, Pattern Recognition and Graphics
Image Processing and Computer Vision
Artificial Intelligence and Robotics
Automation and Robotics - 出版者：Springer Netherlands
- ISSN：1573-7683
文摘
The great flexibility of a view camera allows the acquisition of high quality images that would not be possible any other way. Bringing a given object into focus is however a long and tedious task, although the underlying optical laws are known. A fundamental parameter is the aperture of the lens entrance pupil because it directly affects the depth of field. The smaller the aperture, the larger the depth of field. However a too small aperture destroys the sharpness of the image because of diffraction on the pupil edges. Hence, the desired optimal configuration of the camera is such that the object is in focus with the greatest possible lens aperture. In this paper, we show that when the object is a convex polyhedron, an elegant solution to this problem can be found. It takes the form of a constrained optimization problem, for which theoretical and numerical results are given. The optimization algorithm has been implemented on the prototype of a robotised view camera.