  It is anticipated that the large sky areas covered by planned wide-field weak
lensing surveys will reduce statistical errors to such an extent that
systematic errors will instead become the dominant source of uncertainty. It is
therefore crucial to devise numerical methods to measure galaxy shapes with the
least possible systematic errors. We present a simple "forward deconvolution"
method, gfit, to measure galaxy shapes given telescope and atmospheric
smearings, in the presence of noise. The method consists in fitting a single 2D
elliptical S\'ersic profile to the data, convolved with the point spread
function. We applied gfit to the data proposed in the GRavitational lEnsing
Accuracy Testing 2010 (GREAT10) Galaxy Challenge. In spite of its simplicity,
gfit obtained the lowest additive bias
{($\sqrt{\mathcal{A}}=0.057\times10^{-4}$)} on the shear power spectrum among
twelve different methods and the second lowest multiplicative bias
{($\mathcal{M}/2=0.583\times10^{-2}$)}. It remains that gfit is a fitting
method and is therefore affected by noise bias. However, the simplicity of the
underlying galaxy model combined with the use of an efficient customized
minimization algorithm allow very competitive performances, at least on the
GREAT10 data, for a relatively low computing time.
