  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.
