-For whole experiments, a set of 500 images is randomly extracted
-from the database taken from the BOSS contest~\cite{Boss10}.
+For whole experiments, the whole set of 10000 images
+of the BOSS contest~\cite{Boss10} database is taken.
In this set, each cover is a $512\times 512$
-grayscale digital image.
+grayscale digital image in a RAW format.
+We restrict experiments to
+this set of cover images since this paper is more focussed on
+the methodology than benchmarking.
\subsection{Adaptive Embedding Rate}
The visual quality of the STABYLO scheme is evaluated in this section.
For the sake of completeness, four metrics are computed in these experiments:
the Peak Signal to Noise Ratio (PSNR),
-the PSNR-HVS-M family~\cite{PSECAL07,psnrhvsm11},
-the BIQI~\cite{MB10,biqi11}, and
+the PSNR-HVS-M family~\cite{psnrhvsm11},
+the BIQI~\cite{MB10}, and
the weighted PSNR (wPSNR)~\cite{DBLP:conf/ih/PereiraVMMP01}.
The first one is widely used but does not take into
account the Human Visual System (HVS).
\begin{table*}
\begin{center}
%\begin{small}
-\begin{tabular}{|c|c|c|c|c|c|}
+\begin{tabular}{|c|c|c|c|c|c|c|c|}
\hline
-Schemes & \multicolumn{3}{|c|}{STABYLO} & \multicolumn{2}{|c|}{HUGO}\\
+Schemes & \multicolumn{3}{|c|}{STABYLO} & \multicolumn{2}{|c|}{HUGO}& \multicolumn{2}{|c|}{EAIS}\\
\hline
-Embedding & \multicolumn{2}{|c|}{Adaptive} & Fixed & \multicolumn{2}{|c|}{Fixed} \\
+Embedding & \multicolumn{2}{|c|}{Adaptive} & Fixed & \multicolumn{2}{|c|}{Fixed}& \multicolumn{2}{|c|}{Fixed} \\
\hline
-Rate & + STC & + sample & 10\% & 10\%& 6.35\%\\
+Rate & + STC & + sample & 10\% & 10\%& 6.35\%& 10\%& 6.35\%\\
\hline
-AUMP & 0.39 & 0.33 & 0.22 & 0.50 & 0.50 \\
+AUMP & 0.39 & 0.33 & 0.22 & 0.50 & 0.50 & & \\
\hline
-Ensemble Classifier & 0.47 & 0.44 & 0.35 & 0.48 & 0.49 \\
+Ensemble Classifier & \textbf{0.47} & 0.44 & 0.35 & 0.48 & 0.49 & 0.22 & 0.46 \\
\hline
\end{tabular}
