A Point Spread Function (PSF) engineered imaging system provides functionality at the expense of image distortion. Deconvolution and other post-processing techniques may partially restore the image if the PSF is known. We compare how various phase mask functions (e.g., vortex, axicon, cubic, and circular harmonic) may functionally protect a sensor from a coherent beam, and we discuss the subsequent trade-off between peak irradiance and the integrated modulation transfer function (Strehl ratio). Both experimental and numerical examples demonstrate that the peak irradiance may be suppressed by orders of magnitude without intolerable loss of image fidelity. The design of an optimal phase mask that accomplishes this task is made difficult by the nonlinear relationship between peak irradiance and Strehl. Results from experimental and numerical optimization schemes like simulated annealing, differential evolution, and Nelder-Mead will be compared.
KEYWORDS: Signal to noise ratio, Diffraction, Optical transfer functions, Point spread functions, Optical filters, Computational imaging, Imaging systems, Spatial light modulators, Deconvolution, Modulation transfer functions
A phase-only filter is placed in the pupil plane of an imaging system to engineer a new point spread function with a low peak intensity. Blurred detected images are then reconstructed in post-processing through Wiener Deconvolution. A Differential Evolution algorithm is implemented to optimize these filters for high SNR across the MTF. These filters are tested experimentally using a reflective Spatial Light Modulator (SLM) in the pupil of a system and successfully show the peak intensity reduced 100 times the diffraction limit. Results are compared to expected performance.