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Performance evaluation of adaptive residual interpolation, a tool for inter-layer prediction in H.264/AVC scalable video coding

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Abstract
Inter-layer prediction is the most important technique for improving coding performance in spatial enhancement layers in Scalable Video Coding (SVC). In this paper we discuss Adaptive Residual Interpolation (ART), a new approach to inter-layer prediction of residual data. This prediction method yields a higher coding performance. We integrated the ART tool in the Joint Scalable Video Model software. Special attention was paid to the CABAC context model initialization. Further, the use, complexity, and coding performance of this technology is discussed. Three filters were tested for the interpolation of lower-layer residuals: a bi-linear filter, the H.264/AVC 6-tap filter, and a median filter. Tests have shown that ARI prediction results in an average bit rate reduction of 0.40% for the tested configurations without a loss in visual quality. In a particular test case, a maximum bit rate reduction of 10.10 % was observed for the same objective quality.
Keywords
inter-layer prediction, scalable video coding, coding performance

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Chicago
De Wolf, Koen, Davy De Schrijver, Jan De Cock, Wesley De Neve, and Rik Van de Walle. 2007. “Performance Evaluation of Adaptive Residual Interpolation, a Tool for Inter-layer Prediction in H.264/AVC Scalable Video Coding.” In Lecture Notes in Computer Science, ed. BK Ersboll and KS Pedersen, 4522:740–749. Berlin: Springer.
APA
De Wolf, Koen, De Schrijver, D., De Cock, J., De Neve, W., & Van de Walle, R. (2007). Performance evaluation of adaptive residual interpolation, a tool for inter-layer prediction in H.264/AVC scalable video coding. In B. Ersboll & K. Pedersen (Eds.), LECTURE NOTES IN COMPUTER SCIENCE (Vol. 4522, pp. 740–749). Presented at the 15th Scandinavian Conference on Image Analysis, Berlin: Springer.
Vancouver
1.
De Wolf K, De Schrijver D, De Cock J, De Neve W, Van de Walle R. Performance evaluation of adaptive residual interpolation, a tool for inter-layer prediction in H.264/AVC scalable video coding. In: Ersboll B, Pedersen K, editors. LECTURE NOTES IN COMPUTER SCIENCE. Berlin: Springer; 2007. p. 740–9.
MLA
De Wolf, Koen, Davy De Schrijver, Jan De Cock, et al. “Performance Evaluation of Adaptive Residual Interpolation, a Tool for Inter-layer Prediction in H.264/AVC Scalable Video Coding.” Lecture Notes in Computer Science. Ed. BK Ersboll & KS Pedersen. Vol. 4522. Berlin: Springer, 2007. 740–749. Print.
@inproceedings{416677,
  abstract     = {Inter-layer prediction is the most important technique for improving coding performance in spatial enhancement layers in Scalable Video Coding (SVC). In this paper we discuss Adaptive Residual Interpolation (ART), a new approach to inter-layer prediction of residual data. This prediction method yields a higher coding performance. We integrated the ART tool in the Joint Scalable Video Model software. Special attention was paid to the CABAC context model initialization. Further, the use, complexity, and coding performance of this technology is discussed. Three filters were tested for the interpolation of lower-layer residuals: a bi-linear filter, the H.264/AVC 6-tap filter, and a median filter. Tests have shown that ARI prediction results in an average bit rate reduction of 0.40\% for the tested configurations without a loss in visual quality. In a particular test case, a maximum bit rate reduction of 10.10 \% was observed for the same objective quality.},
  author       = {De Wolf, Koen and De Schrijver, Davy and De Cock, Jan and De Neve, Wesley and Van de Walle, Rik},
  booktitle    = {LECTURE NOTES IN COMPUTER SCIENCE},
  editor       = {Ersboll, BK and Pedersen, KS},
  isbn         = {978-3-540-73039-2},
  issn         = {0302-9743},
  language     = {eng},
  location     = {Aalborg, Denmark},
  pages        = {740--749},
  publisher    = {Springer},
  title        = {Performance evaluation of adaptive residual interpolation, a tool for inter-layer prediction in H.264/AVC scalable video coding},
  volume       = {4522},
  year         = {2007},
}

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