Open AccessLow bit Rate Video Quality Analysis Using NRDPF-VQA Algorithm
Author(s) -
Ch. Subrahmanyam,
Venkata Rao D,
Usha Rani N
Publication year - 2015
Publication title -
international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.277
H-Index - 22
ISSN - 2088-8708
DOI - 10.11591/ijece.v5i1.pp71-77
Subject(s) - computer science , video quality , pevq , subjective video quality , video compression picture types , luminance , coding (social sciences) , metric (unit) , image quality , multiview video coding , artificial intelligence , video processing , motion compensation , rate–distortion optimization , computer vision , video tracking , image (mathematics) , mathematics , statistics , operations management , economics
In this work, we propose NRDPF-VQA (No Reference Distortion Patch Features Video Quality Assessment) model aims to use to measure the video quality assessment for H.264/AVC (Advanced Video Coding). The proposed method takes advantage of the contrast changes in the video quality by luminance changes. The proposed quality metric was tested by using LIVE video database. The experimental results show that the new index performance compared with the other NR-VQA models that require training on LIVE video databases, CSIQ video database, and VQEG HDTV video database. The values are compared with human score index analysis of DMOS.