Smart Depth of Field Optimization Applied to a Robotised View Camera

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.