Detection of region of interest and its application in video image quality assessment

The detection of region of interest(ROI) in video content is analyzed by the subjective eye-tracking experiment and Itti's objective model. For eye-tracking experiments, the time synchronization problem between video content and the data obtained by the eye-tracking experiments is discussed to obtain the subjective weighting matrix of ROI;for Itti's model,the optimization of the number of interesting areas is evaluated to deduce the objective weighting matrix of ROI.These two matrices are integrated into the traditional peak signal-to-noise ratio(PSNR) quality assessment metric, the reliability and improvement are discussed. The experimental results show that by optimizing parameters, the application of the ROI obtained from both eye-tracking experiments and Itti's model improves the correlation between the PSNR and subjective assessment while keeping the simplicity.