  A robust post processing technique is mandatory to analyse the coronagraphic
high contrast imaging data. Angular Differential Imaging (ADI) and Principal
Component Analysis (PCA) are the most used approaches to suppress the
quasi-static structure in the Point Spread Function (PSF) in order to revealing
planets at different separations from the host star. The focus of this work is
to apply these two data reduction techniques to obtain the best limit detection
for each coronagraphic setting that has been simulated for the SHARK-NIR, a
coronagraphic camera that will be implemented at the Large Binocular Telescope
(LBT). We investigated different seeing conditions ($0.4"-1"$) for stellar
magnitude ranging from R=6 to R=14, with particular care in finding the best
compromise between quasi-static speckle subtraction and planet detection.
