-\subsection{Image quality}\label{sub:quality}
-The visual quality of the STABYLO scheme is evaluated in this section.
-For the sake of completeness, three metrics are computed in these experiments:
-the Peak Signal to Noise Ratio (PSNR),
-the PSNR-HVS-M family~\cite{psnrhvsm11},
-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).
-The other ones have been designed to tackle this problem.
-
-If we apply them on the running example with the Adaptive and STC strategies,
-the PSNR, PSNR-HVS-M, and wPSNR values are respectively equal to
-68.39, 79.85, and 89.71 for the stego Lena when $b$ is equal to 7.
-If $b$ is 6, these values are respectively equal to
-65.43, 77.2, and 89.35.
-
-
-
-
-\begin{table*}
-\begin{center}
-\begin{small}
-\setlength{\tabcolsep}{3pt}
-\begin{tabular}{|c|c|c||c|c|c|c|c|c|c|c|c|c|}
-\hline
-Schemes & \multicolumn{4}{|c|}{STABYLO} & \multicolumn{2}{|c|}{HUGO}& \multicolumn{2}{|c|}{EAISLSBMR} & \multicolumn{2}{|c|}{WOW} & \multicolumn{2}{|c|}{UNIWARD}\\
-\hline
-Embedding & Fixed & \multicolumn{3}{|c|}{Adaptive (about 6.35\%)} & Fixed &Adaptive & Fixed &Adaptive & Fixed &Adaptive & Fixed &Adaptive \\
-\hline
-Rate & 10\% & + sample & +STC(7) & +STC(6) & 10\%&$\approx$6.35\%& 10\%&$\approx$6.35\%& 10\%&$\approx$6.35\%& 10\%&$\approx$6.35\%\\
-\hline
-PSNR & 61.86 & 63.48 & 66.55 & 63.7 & 64.65 & {67.08} & 60.8 & 62.9&65.9 & 68.3 & 65.8 & 69.2\\
-\hline
-PSNR-HVS-M & 72.9 & 75.39 & 78.6 & 75.5 & 76.67 & {79.6} & 71.8 & 76.0 &
-76.7 & 80.35 & 77.6 & 81.2 \\
-\hline
-wPSNR & 77.47 & 80.59 & 86.43& 86.28 & 83.03 & {88.6} & 76.7 & 83& 83.8 & 90.4 & 85.2 & 91.9\\
-\hline
-\end{tabular}
-\end{small}
-\end{center}
-\caption{Quality measures of steganography approaches\label{table:quality}}
-\end{table*}
-
-
-
-Results are summarized in Table~\ref{table:quality}.
-In this table, STC(7) stands for embedding data in the LSB whereas
-in STC(6), data are hidden in the last two significant bits.
-
-
-Let us give an interpretation of these experiments.
-First of all, the Adaptive strategy produces images with lower distortion
-than the images resulting from the 10\% fixed strategy.
-Numerical results are indeed always greater for the former strategy than
-for the latter one.
-These results are not surprising since the Adaptive strategy aims at
-embedding messages whose length is decided according to a higher threshold
-into the edge detection.
-
-
-If we combine Adaptive and STC strategies
-the STABYLO scheme provides images whose quality is higher than
-the EAISLSBMR's one but lower than the quality of high complexity
-schemes. Notice that the quality of the less respectful scheme (EAILSBMR)
-is lower than 6\% than the one of the most one.
-
-
-% Let us now compare the STABYLO approach with other edge based steganography
-% approaches, namely~\cite{DBLP:journals/eswa/ChenCL10,Chang20101286}.
-% These two schemes focus on increasing the
-% payload while the PSNR is acceptable, but do not
-% give quality metrics for fixed embedding rates from a large base of images.
+% \subsection{Image quality}\label{sub:quality}
+% The visual quality of the STABYLO scheme is evaluated in this section.
+% For the sake of completeness, three metrics are computed in these experiments:
+% the Peak Signal to Noise Ratio (PSNR),
+% the PSNR-HVS-M family~\cite{psnrhvsm11},
+% 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).
+% The other ones have been designed to tackle this problem.
+
+% If we apply them on the running example with the Adaptive and STC strategies,
+% the PSNR, PSNR-HVS-M, and wPSNR values are respectively equal to
+% 68.39, 79.85, and 89.71 for the stego Lena when $b$ is equal to 7.
+% If $b$ is 6, these values are respectively equal to
+% 65.43, 77.2, and 89.35.
+
+
+
+
+% \begin{table*}
+% \begin{center}
+% \begin{small}
+% \setlength{\tabcolsep}{3pt}
+% \begin{tabular}{|c|c|c||c|c|c|c|c|c|c|c|c|c|}
+% \hline
+% Schemes & \multicolumn{4}{|c|}{STABYLO} & \multicolumn{2}{|c|}{HUGO}& \multicolumn{2}{|c|}{EAISLSBMR} & \multicolumn{2}{|c|}{WOW} & \multicolumn{2}{|c|}{UNIWARD}\\
+% \hline
+% Embedding & Fixed & \multicolumn{3}{|c|}{Adaptive (about 6.35\%)} & Fixed &Adaptive & Fixed &Adaptive & Fixed &Adaptive & Fixed &Adaptive \\
+% \hline
+% Rate & 10\% & + sample & +STC(7) & +STC(6) & 10\%&$\approx$6.35\%& 10\%&$\approx$6.35\%& 10\%&$\approx$6.35\%& 10\%&$\approx$6.35\%\\
+% \hline
+% PSNR & 61.86 & 63.48 & 66.55 & 63.7 & 64.65 & {67.08} & 60.8 & 62.9&65.9 & 68.3 & 65.8 & 69.2\\
+% \hline
+% PSNR-HVS-M & 72.9 & 75.39 & 78.6 & 75.5 & 76.67 & {79.6} & 71.8 & 76.0 &
+% 76.7 & 80.35 & 77.6 & 81.2 \\
+% \hline
+% wPSNR & 77.47 & 80.59 & 86.43& 86.28 & 83.03 & {88.6} & 76.7 & 83& 83.8 & 90.4 & 85.2 & 91.9\\
+% \hline
+% \end{tabular}
+% \end{small}
+% \end{center}
+% \caption{Quality measures of steganography approaches\label{table:quality}}
+% \end{table*}
+
+
+
+% Results are summarized in Table~\ref{table:quality}.
+% In this table, STC(7) stands for embedding data in the LSB whereas
+% in STC(6), data are hidden in the last two significant bits.
+
+
+% Let us give an interpretation of these experiments.
+% First of all, the Adaptive strategy produces images with lower distortion
+% than the images resulting from the 10\% fixed strategy.
+% Numerical results are indeed always greater for the former strategy than
+% for the latter one.
+% These results are not surprising since the Adaptive strategy aims at
+% embedding messages whose length is decided according to a higher threshold
+% into the edge detection.
+
+
+% If we combine Adaptive and STC strategies
+% the STABYLO scheme provides images whose quality is higher than
+% the EAISLSBMR's one but lower than the quality of high complexity
+% schemes. Notice that the quality of the less respectful scheme (EAILSBMR)
+% is lower than 6\% than the one of the most one.
+
+
+% % Let us now compare the STABYLO approach with other edge based steganography
+% % approaches, namely~\cite{DBLP:journals/eswa/ChenCL10,Chang20101286}.
+% % These two schemes focus on increasing the
+% % payload while the PSNR is acceptable, but do not
+% % give quality metrics for fixed embedding rates from a large base of images.
Its main advantage is to be much lighter than the so-called
HUGO, WOW, and UNIWARD schemes, the state of the art
steganographic processes.
-Additionally to this effectiveness,
-quite comparable results through noise measures like PSNR-HVS-M
-and weighted PSNR (wPSNR) are obtained.
+% Additionally to this effectiveness,
+% quite comparable results through noise measures like PSNR-HVS-M
+% and weighted PSNR (wPSNR) are obtained.
To achieve the proposed goal, famous experimented
components of signal processing,
coding theory, and cryptography are combined together, leading to
state of the art steganographic tools has shown that our approach
has the lowest computation cost among all.
This justifies the lightweight attribute of our scheme.
-The evaluation of introduced noise measures
-(namely, the PSNR, PSNR-HVS-M, and weighted PSNR),
-and of its embedding through stegenalysers (namely Ensemble Classifier)
+The evaluation of introduced noise and of
+% measures
+% (namely, the PSNR, PSNR-HVS-M, and weighted PSNR), and of
+its embedding through stegenalysers (namely Ensemble Classifier)
have shown that STABYLO is efficient enough to
produce qualitative images and
to face steganalysers.
