Packet Video Error Concealment With Gaussian Mixture Models
| Autor: | Daniel Persson, Thomas Eriksson, Per Hedelin |
|---|---|
| Rok vydání: | 2008 |
| Předmět: |
packet video
Image quality Computer science Gaussian Normal Distribution Video Recording Sensitivity and Specificity video modeling symbols.namesake Signal-to-noise ratio Error concealment Teknik och teknologier Image Interpretation Computer-Assisted Computer Graphics Computer vision Gaussian process Models Statistical Network packet business.industry Reproducibility of Results Estimator Signal Processing Computer-Assisted Video modeling Data Compression Image Enhancement Missing data Mixture model Computer Graphics and Computer-Aided Design Gaussian mixture model (GMM) symbols Engineering and Technology Artificial intelligence Artifacts business Error detection and correction Algorithm Algorithms Software |
| Zdroj: | IEEE Transactions on Image Processing. 17:145-154 |
| ISSN: | 1057-7149 |
| DOI: | 10.1109/tip.2007.914151 |
| Popis: | In this paper, Gaussian mixture modeling is applied toerror concealment for block-based packet video. A Gaussian mixture model for video data is obtained offline and is thereafter utilized online in order to restore lost blocks from spatial and temporal surrounding information. We propose estimators on closed form for missing data in the case of varying available neighboring contexts. Our error concealment strategy increases peak signal-to-noise ratio compared to previously proposed schemes. Examples of improved subjective visual quality by means of the proposed method are also supplied. ©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.Daniel Persson, Thomas Eriksson and Per Hedelin, Packet Video Error Concealment With Gaussian Mixture Models, 2008, IEEE Transactions on Image Processing, (17), 2, 145-154.http://dx.doi.org/10.1109/TIP.2007.914151 |
| Databáze: | OpenAIRE |
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