X-Git-Url: https://bilbo.iut-bm.univ-fcomte.fr/and/gitweb/canny.git/blobdiff_plain/5e6f9e49a26cec4970434722a595a7b44197120f..100ac9908382b8de480dae1fd68829f2a7778b5d:/experiments.tex?ds=sidebyside

diff --git a/experiments.tex b/experiments.tex
index cf8dfa6..a79b1d4 100644
--- a/experiments.tex
+++ b/experiments.tex
@@ -1,3 +1,20 @@
+
+\subsection{Image Quality}
+The visual quality of the STABYLO scheme is evaluated in this section.
+Three metrics are computed in these experiments : 
+the Peak Signal to Noise Ratio (PSNR), 
+the PSNR-HVS-M~\cite{PSECAL07,psnrhvsm11} and the BIQI~\cite{MB10,biqi11}.
+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.
+
+
+
+biqi = 28.3
+psnr-hvs-m= 78,6
+psnr-hvs= 67.3
+
+
 \subsection{Steganalysis}
 
 
@@ -15,3 +32,7 @@ In the latter, the authors show that the
 machine learning step, (which is often
 implemented as support vector machine)
 can be a favourably executed thanks to an Ensemble Classiï¬ers.
+
+
+
+\JFC{Raphael, il faut donner des rÃ©sultats ici}
\ No newline at end of file
