  Laparoscopic videos can be affected by different distortions which may impact
the performance of surgery and introduce surgical errors. In this work, we
propose a framework for automatically detecting and identifying such
distortions and their severity using video quality assessment. There are three
major contributions presented in this work (i) a proposal for a novel video
enhancement framework for laparoscopic surgery; (ii) a publicly available
database for quality assessment of laparoscopic videos evaluated by expert as
well as non-expert observers and (iii) objective video quality assessment of
laparoscopic videos including their correlations with expert and non-expert
scores.
