deletions | additions       diff --git a/section_Objective_measures_of_quality__.tex b/section_Objective_measures_of_quality__.tex  index 18b9a3e..9f84624 100644  --- a/section_Objective_measures_of_quality__.tex  +++ b/section_Objective_measures_of_quality__.tex 
...
\section{Objective measures of quality of navigation: not yet there}  report usual %\cite{Battisti_2015}\cite{Bosc_2012}\cite{Sandi_Stankovi__2016}\cite{Hanhart_2014}\cite{Bosc_2011_2}  Currently there is a strong need for objective measures of the quality of navigation but not so many solutions have been devised so far. The first approach that has been used is to analyze the behavior of 2D full reference  metrics performance for FVV content. Among the most commonly used quality metrics we can mention PSNR and SSIM. As expected, these metrics are not able to predict the MOS basically due to the presence of artifacts that are typical of this kind of content such as cracks and holes (METTI REF A LAVORO PHILIPPE).  A detailed analysis of the correlation between subjective and objective scores given by some of the most common 2D quality metrics in the state-of-the-art is reported in [6]. In this paper the ….. DESCRIVI and the performed analysis show that the 2D image quality metrics are not able to reliably predict the MOS.   Also the studies carried out in [4]  For this reason the research community started moving  towards new metric...a new hope => dragana and others  \cite{Battisti_2015}\cite{Bosc_2012}\cite{Sandi_Stankovi__2016}\cite{Hanhart_2014}\cite{Bosc_2011_2} the definition of quality metrics able to take into account the characteristics of the FVV content  In [1] an image quality metric, 3DswIM, is presented for synthesized views. It is based on…..  \textbf{The authors in [9] In order to better deal with specific geometric distortions in DIBR synthesized images, we propose multi-scale image quality assessment metric based on morphological filters in multiresolution image decomposition. Introduced non-linear morphological filters maintain important geometric information such as edges across different resolution levels [9]. In the previous work [10], we explored morphological wavelet decompositions for the multiscale metric MW-PSNR, which achieves much higher correlation with human judgment compared to the state-of-the-art image quality measures. We also explored morphological pyramid decomposition in the multiscale metric MP-PSNR [11] which uses mean squared errors of all pyramids’ sub-bands.}