2007•IEEE Transactions on Circuits and Systems for Video TechnologyRequires access

Fast Bit Rate Estimation for Mode Decision of H.264/AVC

Mohammed Golam Sarwer, Lai-Man Po

Open publisher page 52 citations

Abstract

To achieve the highest coding efficiency, H.264/AVC uses rate-distortion optimization technique. This means that the encoder has to code the video by exhaustively trying all the mode combinations including the different intra- and inter-prediction modes. Therefore, the complexity and computation load of video coding in H.264/AVC increase drastically compared to any previous standards. To reduce the complexity of rate-distortion cost computation, we propose a fast bit rate estimation technique to avoid the entropy coding method during intra- and inter-mode decision of H.264/AVC. The estimation method is based on the properties of context-based variable length coding (CAVLC). The proposed rate model predicts the rate of a 4 times 4 quantized residual block using five different tokens of CAVLC. Experimental results demonstrate that the proposed estimation method reduces about 47% of total encoding time on using intra-modes only and saves about 34% of total encoding time on using both inter- and intra-modes with ignorable degradation of coding performance when the fast motion search algorithm is used. When full search motion estimation algorithm is used, the proposed algorithm reduces about 17% of total encoding time.

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What this paper is about

To achieve the highest coding efficiency, H.264/AVC uses rate-distortion optimization technique. This means that the encoder has to code the video by exhaustively trying all the mode combinations including the different intra- and inter-prediction modes. Therefore, the complexity and computation load of video coding in H.264/AVC increase drastically compared to any previous standards. To reduce the complexity of rate-distortion cost computation, we propose a fast bit rate estimation technique to avoid the entropy coding method during intra- and inter-mode decision of H.264/AVC. The estimation method is based on the properties of context-based variable length coding (CAVLC). The proposed rate model predicts the rate of a 4 times 4 quantized residual block using five different tokens of CAVLC. Experimental results demonstrate that the proposed estimation method reduces about 47% of total encoding time on using intra-modes only and saves about 34% of total encoding time on using both inter- and intra-modes with ignorable degradation of coding performance when the fast motion search algorithm is used. When full search motion estimation algorithm is used, the proposed algorithm reduces about 17% of total encoding time.

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Available abstract

To achieve the highest coding efficiency, H.264/AVC uses rate-distortion optimization technique. This means that the encoder has to code the video by exhaustively trying all the mode combinations including the different intra- and inter-prediction modes. Therefore, the complexity and computation load of video coding in H.264/AVC increase drastically compared to any previous standards. To reduce the complexity of rate-distortion cost computation, we propose a fast bit rate estimation technique to avoid the entropy coding method during intra- and inter-mode decision of H.264/AVC. The estimation method is based on the properties of context-based variable length coding (CAVLC). The proposed rate model predicts the rate of a 4 times 4 quantized residual block using five different tokens of CAVLC. Experimental results demonstrate that the proposed estimation method reduces about 47% of total encoding time on using intra-modes only and saves about 34% of total encoding time on using both inter- and intra-modes with ignorable degradation of coding performance when the fast motion search algorithm is used. When full search motion estimation algorithm is used, the proposed algorithm reduces about 17% of total encoding time.

Key concepts: Context-adaptive variable-length coding, Computer science, Context-adaptive binary arithmetic coding, Encoder, Algorithm, Rate–distortion optimization, Motion estimation, Computational complexity theory

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