A fast non-local means algorithm for phase diversity technique to reconstruct high-resolution multi-aperture images

Phase diversity technique (PD) can jointly estimate the wavefront aberration and the target image of an optical imaging system. The PD technique reconstructs images by acquiring a focal plane image of optical system and one or more images with known aberrations (often selected defocus). Due to the simple construction of the optical system, the ability to detect discontinuous co-phase errors, and its applicability to both point sources and extended targets, The PD technique is uniquely suited for spatial target imaging applications, especially for the detection of multi-aperture piston errors. However, in a spatially low-illumination environment, Poisson noise as the main noise source of the imaging system seriously affects the accuracy of the reconstructed images. In this paper, we propose a method of phase diversity technique based on a fast Non-local Means (NLM) algorithm for reconstructing single-aperture images or multi-aperture images. For the two cases of single-aperture imaging and multi-aperture imaging with piston errors in spatial low illumination conditions, the method is used to solve the sensitivity problem of Poisson noise during image reconstruction. Numerical simulation results show that our method has significant improvement in structural similarity of the recovered images compared with the traditional phase diversity technique, and also is faster than the common non-local mean algorithm. The combination of this fast non-local means algorithm which using integral images and the phase diversity technique greatly reduce the computation time. The field experimental results and simulation results show good agreement. The new method would be useful in the AO system with active Poisson noise.