An Efficient Correction Algorithm for Eliminating Image Misalignment Effects on Co-Phasing Measurement Accuracy for Segmented Active Optics Systems

Abstract

The misalignment between recorded in-focus and out-of-focus images using the Phase Diversity (PD) algorithm leads to a dramatic decline in wavefront detection accuracy and image recovery quality for segmented active optics systems. This paper demonstrates the theoretical relationship between the image misalignment and tip-tilt terms in Zernike polynomials of the wavefront phase for the first time, and an efficient two-step alignment correction algorithm is proposed to eliminate these misalignment effects. This algorithm processes a spatial 2-D cross-correlation of the misaligned images, revising the offset to 1 or 2 pixels and narrowing the search range for alignment. Then, it eliminates the need for subpixel fine alignment to achieve adaptive correction by adding additional tip-tilt terms to the Optical Transfer Function (OTF) of the out-of-focus channel. The experimental results demonstrate the feasibility and validity of the proposed correction algorithm to improve the measurement accuracy during the co-phasing of segmented mirrors. With this alignment correction, the reconstructed wavefront is more accurate, and the recovered image is of higher quality.

Co-phasing sparse aperture imaging systems using spatially modulated analytic phase diversity algorithm

“…19 However, LAPD requires focused and defocused images for phase diversity, which brings complexity in the optical path and high requirements for diversity image consistency. 20 We propose a spatially modulated analytic phase diversity algorithm to obtain diversity images using spatially modulated diversity technique. 21 The spatial modulation is realized by shutter control subsystem switching, and the resulting multichannel pictures can be directly used as inputs to the LAPD algorithm, which solves the relative piston errors between sub-apertures.…”