High Quality Video Assessment Using Salient Features

Bhanu Rekha, Ravi Kumar AV

Abstract


An efficient modified video compression HEVC technique based on high quality assessment saliency features presented for the assessment of high quality videos. To create an efficient saliency map we extract global temporal alignment component and robust spatial components. To obtain high quality saliency here, we combine spatial saliency features and temporal saliency features together for different macroblocks in association with transformed residuals. In this way, our saliency model outperforms all the existing techniques. In this paper, we have generated high reconstruction quality video after compression considering SFU dataset. Our experimental results outperforms all the existing techniques in terms of saliency map detection, PSNR and high-resolution quality.


Keywords


Saliency; Quality assessment; HEVC,;PSNR;

Full Text:

PDF


DOI: http://doi.org/10.11591/ijeecs.v7.i3.pp761-772

Refbacks

  • There are currently no refbacks.


Creative Commons License
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.

Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

shopify stats IJEECS visitor statistics