  Intrinsic stellar variability can hinder the detection of shallow transits,
particularly in space-based data. Therefore, this variability has to be
filtered out before running the transit search. Unfortunately, filtering out
the low frequency signal of the stellar variability also modifies the transit
shape. This results in errors in the measured transit depth and duration used
to derive the planet radius, and orbital inclination. We present an evaluation
of the magnitude of this effect based on 20 simulated light curves from the
CoRoT blind exercise 2 (BT2). We then present an iterative filter which uses
the strictly periodic nature of the transits to separate them from other forms
of variability, so as to recover the original transit shape before deriving the
planet parameters. On average with this filter, we improve the estimation of
the transit depth and duration by 15% and 10% respectively.
