Low-cost wavefront coding using coma and a denoising-based deconvolution

Abstract

Wavefront coding (WFC) is a powerful hybrid optical-numerical technique for increasing the depth of focus of imaging systems. It is based on two components: (1) an optical phase element that codifies the wavefront, and (2) a numerical deconvolution algorithm that reconstructs the image. Traditionally, some sophisticated optical WFC designs have been used to obtain approximate focus-invariant point spread functions (PSFs). Instead, we present a simple and low cost solution, implemented on infrared (IR) cameras, which uses a decentred lens inducing coma as an adjustable and removable phase element. We have used an advanced deconvolution algorithm for the image reconstruction, which is very robust against high noise levels. These features allow its application to low cost imaging systems. We show encouraging preliminary results based on realistic simulations using optical PSFs and noise power spectral density (PSD) laboratory models of two IR imaging systems. Without induced optical phase, the reconstruction algorithm improves the image quality in all cases, but it performs poorly when there are both in and out-of-focus objects in the scene. When using our coding/decoding scheme with low-noise detectors, the proposed solution provides high quality and robust recovery even for severe defocus. As sensor noise increases, the image suffers a graceful degradation, its quality being still acceptable even when using highly noisy sensors, such as microbolometers. We have experienced that the amount of induced coma is a key design parameter: while it only slightly affects the in-focus image quality, it is determinant for the final depth of focus.