Foveation-Based Error Resilience and Unequal Error Protection over Mobile Networks
Journal of VLSI Signal Processing Systems
Real-time foveation techniques for low bit rate video coding
Real-Time Imaging
A cross-layer approach for maximizing visual entropy using closed-loop downlink MIMO
EURASIP Journal on Advances in Signal Processing
Robust region-of-interest determination based on user attention model through visual rhythm analysis
IEEE Transactions on Circuits and Systems for Video Technology
Optimal channel adaptation of scalable video over a multicarrier-based multicell environment
IEEE Transactions on Multimedia - Special issue on quality-driven cross-layer design for multimedia communications
High quality, low delay foveated visual communications over mobile channels
Journal of Visual Communication and Image Representation
Foveated mean squared error--a novel video quality metric
Multimedia Tools and Applications
Evaluation of temporal variation of video quality in packet loss networks
Image Communication
A region-based rate-control scheme using inter-layer information for H.264/SVC
Journal of Visual Communication and Image Representation
Modeling motion visual perception for video quality assessment
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Dynamic Bandwidth and Carrier Allocation for Video Broadcast/Multicast Over Multi-Cell Environments
Wireless Personal Communications: An International Journal
Motion characteristic differentiated error concealment
Multimedia Tools and Applications
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Most image and video compression algorithms that have been proposed to improve picture quality relative to compression efficiency have either been designed based on objective criteria such as signal-to-noise-ratio (SNR) or have been evaluated, post-design, against competing methods using an objective sample measure. However, existing quantitative design criteria and numerical measurements of image and video quality both fail to adequately capture those attributes deemed important by the human visual system, except, perhaps, at very low error rates. We present a framework for assessing the quality of and determining the efficiency of foveated and compressed images and video streams. Image foveation is a process of nonuniform sampling that accords with the acquisition of visual information at the human retina. Foveated image/video compression algorithms seek to exploit this reduction of sensed information by nonuniformly reducing the resolution of the visual data. We develop unique algorithms for assessing the quality of foveated image/video data using a model of human visual response. We demonstrate these concepts on foveated, compressed video streams using modified (foveated) versions of H.263 that are standard-compliant. We rind that quality vs. compression is enhanced considerably by the foveation approach