2009Unpublished venueOpen access

Lagrange multiplier selection for rate-distortion optimization in SVC

Xiang Li, Peter Amon, Andreas Hutter, André Kaup

Open full text 27 citations

Abstract

The Lagrangian multiplier based rate-distortion optimization (RDO) has been widely employed in single layer video coding. During the development of scalable video coding (SVC) extension of H.264/AVC, it was directly applied in a multilayer scenario. However, such an application is not very efficient since the correlation between layers is not considered in the Lagrange multiplier selection. To improve the overall performance, in this paper a new selection algorithm is presented for RDO in SVC. Simulations show that the proposed method outperforms the recent SVC reference software. With a tiny computational cost, average gains of 0.22 dB and 0.35 dB were achieved in the tests of four-layer quality scalability and three-layer spatial scalability, respectively.

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What this paper is about

The Lagrangian multiplier based rate-distortion optimization (RDO) has been widely employed in single layer video coding. During the development of scalable video coding (SVC) extension of H.264/AVC, it was directly applied in a multilayer scenario. However, such an application is not very efficient since the correlation between layers is not considered in the Lagrange multiplier selection. To improve the overall performance, in this paper a new selection algorithm is presented for RDO in SVC. Simulations show that the proposed method outperforms the recent SVC reference software. With a tiny computational cost, average gains of 0.22 dB and 0.35 dB were achieved in the tests of four-layer quality scalability and three-layer spatial scalability, respectively.

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Available abstract

The Lagrangian multiplier based rate-distortion optimization (RDO) has been widely employed in single layer video coding. During the development of scalable video coding (SVC) extension of H.264/AVC, it was directly applied in a multilayer scenario. However, such an application is not very efficient since the correlation between layers is not considered in the Lagrange multiplier selection. To improve the overall performance, in this paper a new selection algorithm is presented for RDO in SVC. Simulations show that the proposed method outperforms the recent SVC reference software. With a tiny computational cost, average gains of 0.22 dB and 0.35 dB were achieved in the tests of four-layer quality scalability and three-layer spatial scalability, respectively.

Key concepts: Lagrange multiplier, Scalability, Rate–distortion optimization, Computer science, Scalable Video Coding, Coding (social sciences), Mathematical optimization, Rate–distortion theory

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