{\em frthre} copies the input image $A$ in the output $B$ and makes a thresold 
of the pixel's values according the rule:
\index{denoising!thresholding}
\[
B(x,y) = \left\{
\begin{array}{ll}
 0 & \mbox{ if } |A(x,y)| \leq \mbox{\tt noise}; \\
 A(x,y) - \mbox{sgn}(A(x,y)) \times \mbox{\tt noise} & \mbox{elsewhere.} 
\end{array}
\right.
\]
Where \verb+noise+ is the absolute maximal value of the noise (noise level).

In~\cite{donoho.johnstone:ideal}, it is proved that this simple threshold rule is one 
of the best estimator for recovering a noisy image (additive noise) using the MiniMax 
error, when the coefficients in $A$ and $B$ are coordinates in an orthonormal basis
(such as wavelet basis).

