té

[canny.git] / experiments.tex

diff --git a/experiments.tex b/experiments.tex
index 11af8445054232319128fa8a678dcccd73c199ca..b952faecd3b00ceeed291641cea5e1db2eac81b5 100644 (file)
--- a/experiments.tex
+++ b/experiments.tex
@@ -1,12 +1,39 @@
 
 \subsection{Image Quality}
 The visual quality of the STABYLO scheme is evaluated in this section.
 
 \subsection{Image Quality}
 The visual quality of the STABYLO scheme is evaluated in this section.

-Three metrics are computed in these experiments : 
+Four metrics are computed in these experiments : 

 the Peak Signal to Noise Ratio (PSNR), 
 the Peak Signal to Noise Ratio (PSNR), 

-the PSNR-HVS-M~\cite{PSECAL07,psnrhvsm11} and the BIQI~\cite{MB10,biqi11}.
+the PSNR-HVS-M familly~\cite{PSECAL07,psnrhvsm11} , 
+the BIQI~\cite{MB10,biqi11} and 
+the weigthed PSNR (wPSNR)~\cite{DBLP:conf/ih/PereiraVMMP01}.

 The first one is widely used but does not take into
 account Human Visual System (HVS).
 The first one is widely used but does not take into
 account Human Visual System (HVS).

-The two last ones have been designed to tackle this problem.
+The other last ones have been designed to tackle this problem.
+
+\begin{table}
+\begin{center}
+\begin{tabular}{|c|c|c|}
+\hline
+Embedding rate &  Adaptive 
+10 \% &  \\
+\hline
+PSNR &      &      \\
+\hline
+PSNR-HVS-M & 78.6  & 72.9 \\
+\hline
+BIQI & 28.3 & 28.4 \\
+\hline
+wPSNR & 86.43& 77.47 \\
+\hline
+\end{tabular}
+\end{center}
+\caption{Quality measeures of our steganography approach\label{table:quality}} 
+\end{table}
+
+
+Compare to the Edge Adpative scheme detailed in~\cite{Luo:2010:EAI:1824719.1824720}, our both wPSNR and PSNR values are always higher than their ones.
+
+\JFC{comparer aux autres approaches}

 
 
 
 
 
 


@@ -30,4 +57,21 @@ can be a favourably executed thanks to an Ensemble Classifiers.
 
 
 
 
 
 

-\JFC{Raphael, il faut donner des résultats ici}
\ No newline at end of file
+\begin{table}
+\begin{center}
+\begin{tabular}{|c|c|c|c|}
+Shemes & \multicolumn{2}{|c|}{STABYLO} & HUGO\\
+\hline
+Embedding rate &  Adaptive & 10 \% &  10 \%\\
+\hline
+AUMP & 0.39  & 0.22     &  0.50     \\
+\hline
+Ensemble Classifier &   &      &      \\
+
+\hline
+\end{tabular}
+\end{center}
+\caption{Steganalysing STABYLO\label{table:steganalyse}} 
+\end{table}
+
+