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High-contrast imaging for the detection and characterization of exoplanetsrelies on the instrument's capability to block out the light of the host star.Some current post-processing methods for calibrating out the residual specklesuse information redundancy offered by multispectral imaging but do not use anyprior information on the origin of these speckles. We investigate whetheradditional information on the system and image formation process can be used tomore finely exploit the multispectral information. We developed an inversionmethod in a Bayesian framework that is based on an analytical imaging model toestimate both the speckles and the object map. The model links the instrumentalaberrations to the speckle pattern in the image focal plane, distinguishingbetween aberrations upstream and downstream of the coronagraph. We propose andvalidate several numerical techniques to handle the difficult minimizationproblems of phase retrieval and achieve a contrast of 10^6 at 0.2 arcsec fromsimulated images, in the presence of photon noise. This opens up the thepossibility of tests on real data where the ultimate performance may overridethe current techniques if the instrument has good and stable coronagraphicimaging quality. This paves the way for new astrophysical exploitations or evennew designs for future instruments.

Simultaneous exoplanet detection and instrument aberration retrieval in multispectral coronagraphic imaging