suppression des refs au PSNR

[canny.git] / experiments.tex

diff --git a/experiments.tex b/experiments.tex
index 5ba43dfa16ae206dcee8557c46adc9ef457b7645..22900c0ec35afc7f4a5dc8937e27b2da0e0110f7 100644 (file)
--- a/experiments.tex
+++ b/experiments.tex
@@ -1,5 +1,5 @@
 First of all, the whole code of STABYLO can be downloaded
 First of all, the whole code of STABYLO can be downloaded

-\footnote{\url{http://members.femto-st.fr/raphael-couturier/stabylo/}}.
+\footnote{\url{http://http://members.femto-st.fr/jf-couchot/en/stabylo}}.

 For all the experiments, the whole set of 10,000 images 
 of the BOSS contest~\cite{Boss10} database is taken. 
 In this set, each cover is a $512\times 512$
 For all the experiments, the whole set of 10,000 images 
 of the BOSS contest~\cite{Boss10} database is taken. 
 In this set, each cover is a $512\times 512$


@@ -62,80 +62,80 @@ this cover with respect to this embedding rate.
 
  
 
 
  
 

-\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.
+% \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.
+% 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$6.35\%\\ 
-\hline
-PSNR & 61.86 & 63.48 &  66.55  &  63.7  & 64.65 & {67.08} & 60.8 & 62.9&65.9 & 68.3 & 65.8 & 69.2\\ 
-\hline
-PSNR-HVS-M & 72.9 & 75.39 & 78.6  & 75.5  & 76.67 & {79.6} & 71.8  & 76.0 &
-76.7 & 80.35 & 77.6 & 81.2 \\
-\hline
-wPSNR & 77.47 & 80.59 & 86.43& 86.28  & 83.03 & {88.6} & 76.7 & 83& 83.8 & 90.4 & 85.2 & 91.9\\ 
-\hline
-\end{tabular}
-\end{small}
-\end{center}
-\caption{Quality measures of steganography approaches\label{table:quality}}
-\end{table*}
+% \begin{table*}
+% \begin{center}
+% \begin{small}
+% \setlength{\tabcolsep}{3pt}
+% \begin{tabular}{|c|c|c||c|c|c|c|c|c|c|c|c|c|}
+% \hline
+% Schemes & \multicolumn{4}{|c|}{STABYLO} & \multicolumn{2}{|c|}{HUGO}& \multicolumn{2}{|c|}{EAISLSBMR} & \multicolumn{2}{|c|}{WOW} & \multicolumn{2}{|c|}{UNIWARD}\\
+% \hline
+% Embedding &   Fixed & \multicolumn{3}{|c|}{Adaptive (about 6.35\%)} &  Fixed &Adaptive & Fixed &Adaptive & Fixed &Adaptive & Fixed &Adaptive \\
+% \hline
+% Rate &   10\% &  + sample &  +STC(7) & +STC(6) &  10\%&$\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. 
+% 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.  
+% 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.
+% 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. 
+% % 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. 

 
 
 
 
 
 


@@ -205,10 +205,10 @@ as far as we know.
 However by combining Adaptive and STC strategies
 our approach obtains similar results than the ones of these schemes.
 
 However by combining Adaptive and STC strategies
 our approach obtains similar results than the ones of these schemes.
 

-Compared to EAILSBMR, we obtain better results when the strategy is 
+Compared to EAILSBMR, we obtain similar
+results when the strategy is 

 Adaptive. 
 Adaptive. 

-However due to its 
-huge number of integration features, it is not lightweight.
+However due to its huge number of integration features, it is not lightweight.

 
 All these numerical experiments confirm 
 the objective presented in the motivations:
 
 All these numerical experiments confirm 
 the objective presented in the motivations: