In order to enhance accuracy of astrophysical estimates obtained on Adaptive-optics ( AO ) images , such as photometry and astrometry , we investigate a new concept to constrain the Point Spread Function ( PSF ) model called PSF Reconstruction and Identification for Multi-sources characterization Enhancement ( PRIME ) , that handles jointly the science image and the AO control loop data .
We present in this paper the concept of PRIME and validate it on Keck II telescope NIRC2 images .
We show that by calibrating the PSF model over the scientific image , PSF reconstruction achieves 1 % and 3 mas of accuracy on respectively the Strehl-ratio and the PSF full width at half maximum .
We show on NIRC2 binary images that PRIME is sufficiently robust to noise to retain photometry and astrometry precision below 0.005 mag and 100 \mu as on a m _ { H } = 14 mag object .
Finally , we also validate that PRIME performs a PSF calibration on the triple system Gl569BAB which provides a separation of 66.73 \pm 1.02 and a differential photometry of 0.538 \pm 0.048 , compared to the reference values obtained with the extracted PSF which are 66.76 mas \pm 0.94 and 0.532 mag \pm 0.041 .