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 (ARI), a new approach to inter-layer prediction of residual data. This prediction method yields a higher coding performance. We integrated the ARI 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. © Springer-Verlag Berlin Heidelberg 2007.

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APA

De Wolf, K., 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 Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4522 LNCS, pp. 740–749). Springer Verlag. https://doi.org/10.1007/978-3-540-73040-8_75

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