Title
Modeling of Rate and Perceptual Quality of Compressed Video as Functions of Frame Rate and Quantization Stepsize and Its Applications
Abstract
This paper first investigates the impact of frame rate and quantization on the bit rate and perceptual quality of compressed video. We propose a rate model and a quality model, both in terms of the quantization stepsize and frame rate. Both models are expressed as the product of separate functions of quantization stepsize and frame rate. The proposed models are analytically tractable, each requiring only a few content-dependent parameters. The rate model is validated over videos coded using both scalable and nonscalable encoders, under a variety of encoder settings. The quality model is validated only for a scalable video, although it is expected to be applicable to a single-layer video as well. We further investigate how to predict the model parameters using the content features extracted from original videos. Results show accurate bit rate and quality prediction (average Pearson correlation ${>}{0.99}$) can be achieved with model parameters predicted using three features. Finally, we apply rate and quality models for rate-constrained scalable bitstream adaptation and frame rate adaptive rate control. Simulations show that our model-based solutions produce better video quality compared with conventional video adaptation and rate control.
Year
DOI
Venue
2012
10.1109/TCSVT.2011.2177143
IEEE Transactions on Circuits and Systems for Video Technology
Keywords
Field
DocType
scalable video coding (svc),rate control,single-layer video,perceptual quality model,scalable video adaptation,scalable encoders,nonscalable encoders,quantisation (signal),data compression,encoder settings,content-dependent parameters,video compression perceptual quality,rate model,feature extraction,quantization stepsize,video coding,bit rate quantization,video adaptation,quality prediction,h.264/avc,content feature,frame rate adaptive rate control,rate-constrained scalable bitstream adaptation,model-based solutions,prediction model,predictive models,video quality,quantization,spatial resolution,scalable video coding
Computer vision,Pattern recognition,Computer science,Feature extraction,Artificial intelligence,Encoder,Frame rate,Bitstream,Quantization (signal processing),Data compression,Video quality,Scalability
Journal
Volume
Issue
ISSN
22
5
1051-8215
Citations 
PageRank 
References 
47
1.65
10
Authors
4
Name
Order
Citations
PageRank
Zhan Ma157645.61
Meng Xu2644.95
Yen-Fu Ou31959.70
Yao Wang43757312.89