Frame-layer rate control algorithm for H.264 based on improved frame MAD

Ziguan Cui; Ningzhong Liu

doi:10.1117/12.774798

14 November 2007 Frame-layer rate control algorithm for H.264 based on improved frame MAD

Ziguan Cui, Ningzhong Liu

Proceedings Volume 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications; 67904N (2007) https://doi.org/10.1117/12.774798
Event: International Symposium on Multispectral Image Processing and Pattern Recognition, 2007, Wuhan, China

Abstract

In this paper, we present an improved frame layer rate control algorithm for H.264/AVC video coding standard. An important step in many existing rate control algorithms is to determine the target bits for each P frame. In the standard rate control scheme of H.264, the target bit number is a weighted combination of remaining bits and bits calculated from buffer regulation. The problem is that the remaining bits are allocated to all non-coded frames equally. This will cause non-uniform image quality over a video sequence. To overcome this disadvantage, first we define frame complexity ratio (FC_ratio) as a measure for global frame encoding complexity and then allocate initial target bit according to its FC_ratio. We define FC_ratio as a weighted combination of motion complexity and texture complexity which can predict current frame complexity more accurately using the statistics of previously encoded frame and the texture information of current frame. Experiment results show that our improved algorithm can acquire more accurate quantization parameter (QP) for each P frame through the quadratic rate-distortion (R-D) model, achieve an average PSNR gain of about 0.28 dB and meanwhile effectively alleviate the buffer's fluctuating range and frame PSNR variation.

Citation Download Citation

Ziguan Cui and Ningzhong Liu "Frame-layer rate control algorithm for H.264 based on improved frame MAD", Proc. SPIE 6790, MIPPR 2007: Remote Sensing and GIS Data Processing and Applications; and Innovative Multispectral Technology and Applications, 67904N (14 November 2007); https://doi.org/10.1117/12.774798

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KEYWORDS

Computer programming

Video

Detection and tracking algorithms

Video coding

Motion models

Image quality standards

Quantization

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