ABSTRACT
In this paper we use our derived approximate representation of the modulation transfer function to analytically solve the problem of the extension of the depth of field for two cases of interest: uniform quality imaging and task-based imaging. We derive the optimal result for each case as a function of the problem specifications. We also compare the two different imaging cases and discuss the advantages of using our optimization approach for each case. We also show how the analytical solutions given in this paper can be used as a convenient design tool as opposed to previous lengthy numerical optimizations.
ABSTRACT
We analyze the signal-to-noise ratio (SNR) of arbitrary imaging systems in the presence of defocus. The modulation transfer function (MTF) and the mean SNR are combined to calculate the spatial-frequency spectrum of the SNR (the spectral SNR). Computational imaging methods are used for extending the depth of field (DOF) of the system. The DOF of a task-specific imaging system is defined as the range of defocus that causes the spectral SNR to drop below a minimum value within a band of spatial frequencies of interest. We introduce the polar-SNR plot as a tool for visualizing the spectral SNR of defocused imaging systems with asymmetric pupil functions. As an example, we perform the analysis of an imaging system used for biometric iris recognition.
ABSTRACT
The use of the human iris as a biometric has recently attracted significant interest in the area of security applications. The need to capture an iris without active user cooperation places demands on the optical system. Unlike a traditional optical design, in which a large imaging volume is traded off for diminished imaging resolution and capacity for collecting light, Wavefront Coded imaging is a computational imaging technology capable of expanding the imaging volume while maintaining an accurate and robust iris identification capability. We apply Wavefront Coded imaging to extend the imaging volume of the iris recognition application.
