Regular papers

Quantifying the 2.5D imaging performance of digital holographic systems

¹ Institut für Mikro- und Nanotechnologien, Macro-Nano, Fachgebiet Optik Design, Technische Universit¨at Ilmenau, Postfach 100565, 98684 Ilmenau, Germany
² Instituto de Ciencias Físicas, Universidad Nacional Autónoma de Mexico, Avenida Universidad S/N, Colonia Chamilpa Cuernavaca Morelos, C.P. 62210 Mexico
³ Department of Computer Science, National University of Ireland, Maynooth, Co. Kildare, Ireland The Callan Institute, National University of Ireland, Maynooth, Co. Kildare, Ireland
⁴ UCD Communications and Optoelectronic Research Centre, University College Dublin, Belfield, Dublin 4, Ireland
⁵ SFI Strategic Research Cluster in Solar Energy Conversion, University College Dublin, Belfield, Dublin 4, Ireland
⁶ School of Electrical Electronic and Mechanical Engineering, College of Engineering, Mathematical and Physical Sciences, University College Dublin, Belfield, Dublin 4, Ireland

^* damien-peter.kelly@tu-ilmenau.de

Received: 17 September 2010

Abstract

Digital holographic systems are a class of two step, opto-numerical, pseudo-three-dimensional imaging techniques. The role of the digital camera in limiting the resolution and field of view of the reconstructed image, and the interaction of these limits with a general optical system is poorly understood. The linear canonical transform describes any optical system consisting of lenses and/or free space in a unified manner. Expressions derived using this transform are parametrised in terms of the parameters of the optical system, as well as those of the digital camera: aperture size, pixel size and pixel pitch. We develop rules of thumb for selecting an optical system to minimise mean squared error for given input and digital camera parameters. In the limit, our results constitute a point spread function analysis. The results presented in this paper will allow digital holography practitioners to select an optical system to maximise the quality of their reconstructed image using a priori knowledge of the camera and object.