Correcting Axial Chromatic Aberration in a Fixed Focal Plane, Near-infrared Imaging System

Abstract

Distortions of an image in an optical imaging system due to differing indices of refraction for each wavelength of light are categorized as chromatic aberration (CA). Different magnifications at each wavelength result in geometric distortion of images known as Lateral Chromatic Aberration (LCA), while differing focal planes result in blurring of specific wavelengths known as Axial Chromatic Aberration (ACA). The current study reviews methods and tests an algorithm that can compensate for the substantial ACA that occurs in a fixed focal plane near-infrared imaging system. The system examined employs a liquid crystal tunable filter (LCTF) based hyperspectral imaging system capable of automatically acquiring a hyperspectral data cube in the 900 - 1700 nm range. The experiments use a test pattern image containing multiple grids with a known geometry to establish ground truth for the acquired image. Data shows that ACA distortion of images at 1600 nm with imaging system properly focused at 1000 nm is visibly severe. The proposed method to correct for ACA is based on deconvolution theory and uses a geometric model in favor of a physical model to estimate the point spread function (PSF). Experimental results indicate that the approach taken is feasible and robust.