Paper Info
Title
A Novel No-Reference PSNR Estimation Method With Regard to Deblocking Filtering Effect in H.264/AVC Bitstreams
Abstract
Peak signal-to-noise ratio (PSNR) monitoring is an important application for video quality assessment of video systems at the receiver sides where no-reference PSNR estimation is essential. Most of the PSNR estimation methods for H.264/AVC bitstreams ignore or do not consider the effect of deblocking filtering. Instead, they only focus on estimating the mean squared error (MSE) due to quantization. However, the PSNR estimation affected by deblocking filtering cannot be negligible for sequences of large picture resolutions. In this paper, we first present an MSE estimation method on H.264/AVC bitstreams by considering the deblocking filtering effect so that more accurate PSNR estimation can be made. For this, the total MSE between the original and reconstructed frames is separated into two terms for PSNR estimation: one due to quantization error and the other due to the deblocking filtering effect in H.264/AVC. In the proposed PSNR estimation, the contribution of deblocking filtering to the total MSE is quantified by a compensation factor of each encoded picture type between the original and the deblocked frames. Experimental results show that the proposed method effectively reflects the contribution of deblocking filtering to PSNR estimation, thus yielding more accurate PSNR estimates.
Year
DOI
Venue
2014
10.1109/TCSVT.2013.2255425
IEEE Trans. Circuits Syst. Video Techn.
Keywords
Field
DocType
no-reference visual quality assessment,no-reference psnr estimation method,image resolution,image reconstructed frame separation,large picture resolution sequence,quantisation (signal),quantization error,estimation theory,mean squared error estimation,deblocking filtering effect,video quality assessment,image reconstruction,mse estimation,video coding,image sequences,h.264-avc bitstream,peak signal-to-noise ratio,filtering theory,peak signal-to-noise ratio (psnr) estimation,compensation,deblocking filter,compensation factor,h264/avc,mean square error methods
Iterative reconstruction,Computer vision,Pattern recognition,Computer science,Mean squared error,Filter (signal processing),Artificial intelligence,Estimation theory,Quantization (signal processing),Video quality,Image resolution,Deblocking filter
Journal
Volume
Issue
ISSN
24
2
1051-8215
Citations 
PageRank 
References 
2
0.37
6
Authors
2
Name
Order
Citations
PageRank
Taeyoung Na172.19
Munchurl Kim285868.28