Martin Coath edited section_Methods_subsection_Algorithm_For__.tex  about 8 years ago

Commit id: 242fd40fc6c8703a3893d66b421ed7317cdb3aac

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\item hence the working window size is $n = 2 \cdot m+1$ even when this differs from $w$ by one  \item assemble the horizontal vector $\vec{k}_{h}$ of values for a window of $n$ pixels $k_{[i,j-m \: : \: i,j+m]}$  \item repeat with $\vec{k}_{v}$, a vector of values for a vertical window of $n$ pixels $k_{[i-m,j \: : \: i+m,j]}$  \item both vectors are normalized, so they can be treated as distributions, and the Skewness $\gamma$ skewness  of each distribution (\textit{i.e.} a measure of the asymmetry in the gray-scale values in both direction) is calculated, $\gamma_h$ and $\gamma_v$ \item the \textsc{skv} value of the pixel $\gamma_{i,j}$ is the mean of the two values $\frac{\gamma_j + \gamma_i}{2}$  \end{enumerate}