Paper Info
Title
A No-Reference Video Quality Assessment Based On Laplacian Pyramids
Abstract
This paper presents an approach to predict the quality of compressed videos with content of natural scenes. The method is focused on measuring the distortion of compressed video without reference. There are two main steps of the proposed method: measuring distortion and predicting video quality. Each frame of the distorted video sequence is first decomposed to an N-subband Laplacian pyramid, then their intra-subband and inter-subband statistical features are fully exploited. Three intra-subband features and three inter-subband features are taken as inputs of the prediction model. Its output is a single score as the predicted video quality. The performance of the proposed method is evaluated on the LIVE video database and the LIVE mobile video database. Results show that the predicted quality scores are well correlated with the mean opinion scores associated to the subjective assessment.
Year
Venue
Keywords
2013
2013 20TH IEEE INTERNATIONAL CONFERENCE ON IMAGE PROCESSING (ICIP 2013)
Image/video quality assessment, no-reference, natural scenes, Laplacian pyramid
Field
DocType
ISSN
Computer vision,Block-matching algorithm,Video post-processing,Pattern recognition,Computer science,Motion compensation,Multiview Video Coding,Artificial intelligence,Video quality,Video denoising,Video compression picture types,Rate–distortion optimization
Conference
1522-4880
Citations 
PageRank 
References 
3
0.37
5
Authors
4
Name
Order
Citations
PageRank
Kongfeng Zhu1221.36
Keigo Hirakawa234028.65
Vijayan K. Asari3782107.90
Dietmar Saupe4110485.80