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+\section{Moving Average Filter}
+% Basic box filter formula
+% Recursive form
+% Gauss Blur Filter
+% Repetitive Box filter to approx Gauss
+% Simple multipass, n/m approach, extended box filter
+The moving average filter is a simplistic filter which takes an input function $x$ and produces a second function $y$.
+A single output value is computed by taking the average of a number of values symmetrical around a single point in the input.
+The number of values in the average can also be seen as the width $w=2r+1$, where $r$ is the \qq{radius} of the filter.
+The computation of an output value using a moving average filter of radius $r$ is defined as
+\begin{equation}
+\label{eq:symMovAvg}
+y[i]=\frac{1}{2r+1} \sum_{j=-r}^{r}x[i+j] \text{.}
+\end{equation}
+
+It is well-known that a moving average filter can approximate a Gaussian filter by repetitive recursive computations.
+
+
+
+As is known the Gaussian filter is parametrized by its standard deviation $\sigma$.
+To approximate a Gaussian filter one needs to express a given $\sigma$ in terms of moving average filters.
+