ABSTRACT
This Letter examines sharpness metric maximization methods on 3D images obtained at Table Mountain, Colorado. We employ multi-wavelength 3D imaging with digital holography and a pilot tone to obtain the aberrated images and use sharpness metric maximization to correct the aberrated images with both pupil-plane and multi-plane corrections. Image quality improves when sharpness metric maximization is used and particularly with multi-plane correction.
ABSTRACT
Using wave-optics simulations, this paper defines what subaperture sampling effectively means for digital-holography applications involving atmospheric turbulence. Throughout, we consider the on-axis phase shifting recording geometry (PSRG) and off-axis PSRG, both with the effects of sensor noise. The results ultimately show that (1) insufficient subaperture sampling manifests as an efficiency loss that limits the achievable signal-to-noise ratio and field-estimated Strehl ratio; (2) digital-holography applications involving atmospheric turbulence require at least three focal-plane array (FPA) pixels per Fried coherence length to meet the Maréchal criterion; and (3) off-axis PSRG is a valid and efficient implementation with minor losses, as compared to on-axis PSRG. Such results will inform future research efforts on how to efficiently use the available FPA pixels.
ABSTRACT
Sharpness metric maximization is a method for reconstructing coherent images that have been aberrated due to distributed-volume turbulence. This method places one or more corrective phase screens in the digital-propagation path that serve to increase overall sharpness of the image. As such, this study uses sharpness metric maximization on 3D irradiances obtained via frequency-diverse digital holography. We vary the number of corrective phase screens in the propagation path and sharpen images of a realistic, extended object via multi-plane sharpness metric maximization. The results indicate that image reconstruction is possible when using fewer corrective screens than aberrating screens, but that image quality increases with a greater number of corrective screens.
ABSTRACT
In this paper, we quantify the benefits of compensated-beacon adaptive optics (CBAO) relative to uncompensated-beacon adaptive optics (UBAO) using wave-optics simulations. Throughout, we present results for both the Shack-Hartmann wavefront sensor (SH-WFS) and the digital-holographic wavefront sensor (DH-WFS). Given weak to moderately strong scintillation conditions, the results show that the two noiseless sensors offer similar performance in terms of the peak Strehl ratio when using similar subaperture sampling and least-squares phase reconstruction. Specifically, CBAO leads to an average performance boost of 17% for the SH-WFS and 26% for the DH-WFS relative to UBAO for the turbulence scenarios studied here.
ABSTRACT
This paper uses wave-optics and signal-to-noise models to explore the estimation accuracy of digital-holographic detection in the off-axis pupil plane recording geometry for deep-turbulence wavefront sensing. In turn, the analysis examines three important parameters: the number of pixels across the width of the focal-plane array, the window radius in the Fourier plane, and the signal-to-noise ratio. By varying these parameters, the wave-optics and signal-to-noise models quantify performance via a metric referred to as the field-estimated Strehl ratio, and the analysis leads to a method for optimal windowing of the turbulence-limited point spread function. Altogether, the results will allow future research efforts to assess the number of pixels, pixel size, pixel-well depth, and read-noise standard deviation needed from a focal-plane array when using digital-holographic detection in the off-axis pupil plane recording geometry for estimating the complex-optical field when in the presence of deep turbulence and detection noise.
ABSTRACT
In this paper, we present experimental results for image reconstruction, with isoplanatic phase-error correction, from single-shot digital holography data. We demonstrate the utility of using a model-based iterative reconstruction (MBIR) algorithm to jointly compute the maximum a posteriori estimates of the phase errors and the real-valued object reflectance function. Specifically, we show that the MBIR algorithm is robust to noise and phase errors over a range of conditions.
