Optimizing optical precision of an image using curved focal plane technology
Sujay Swain, Sudhish Swain, Dianne L. Poster, Michael T. Postek
The quality of an image captured by the human eye is typically better than that obtained relative to artificial images created by cameras or telescopes. This is because humans have curved retinas. In contrast, conventional imaging cameras have at sensors that are not well matched to the curved focal surfaces of a camera lens or telescope objective. Thus, the image cannot be at the same focus across the entire sensor field of view. It is hypothesized that as the surface of the sensor approaches the curvature of the camera lens or telescope, the image quality increases. To test this, a commercially available ray tracing software was used. The curvatures were varied from at (0 mm) to 12 mm. As the curvature reached 9 mm, the Petzval curvature, the quality of the captured images from the camera significantly improved. However, as the curvature increased beyond 9 mm, the quality of the artificial image decreased. In addition, a simulation of a classical Cassegrain telescope was also made. For the telescope, the curvatures were varied from 0 mm to 500 mm. As the curvature approached the telescope's focal surface curvature of 350 mm, the distortion decreased. In addition to the optical simulations, two images were generated: one with a camera and the other by a reconstruction process. The latter was reconstructed by using the central part of images taken along that curve to create an image. A comparison of these images demonstrates the superior image produced with the latter method. Devices such as cameras and telescopes with curved focal planes produce images with higher quality than those produced using devices equipped with focal planes.
Proc. SPIE 11693, Photonic Instrumentation Engineering VIII
, Swain, S.
, , D.
and Postek, M.
Optimizing optical precision of an image using curved focal plane technology, Proc. SPIE 11693, Photonic Instrumentation Engineering VIII, Bellingham, WA, [online], https://dx.doi.org/10.1117/12.2583122, https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=931746
(Accessed September 17, 2021)