基于相关性分析的MVC比特分配算法

针对目前尚未深入研究多视点视频编码（Multi—view Video Coding，MVC）码率控制的问题，提出了一种基于相关性分析的多视点视频编码码率控制算法。该算法的核心是先根据视差预测和运动预测的结构关系，将所有图像分成6种类型的编码帧，并改进二项式率失真模型，然后根据多视点视频相关性分析在各个视点之间进行合理的码率分配，将码率控制分成4层结构进行多视点视频编码的码率控制。其中，帧层码率控制考虑分层B帧等因素分配码率，基本单元层码率控制根据宏块的内容复杂度采用不同的量化参数。实验结果表明该码率控制算法实际码率与目标码率平均误差能控制0．6％。

Bit allocation algorithm for multi-view video coding based on correlation analysis

Current multi-view Video Coding（MVC） reference model in Joint Video Team（JVT） does not provide efficient rate control schemes, this paper proposes a rate control algorithm for MVC based on correlation analysis. The proposed algorithm classifies each picture into six frame types based on the relation between disparity prediction and temporal prediction estimation and also improves the estimation accuracy of the Mean Absolute Difference （MAD）. The proposed algorithm consists of four levels to control the rate bits more accurately. This paper reasonably allocates bit-rate among views based on the correlation analysis. In a frame ~ayer, it performs bit allocation according to the hierarchical B-frame. In a basic unit layer, it selects quantization parameter adaptively according to the content complexity of the macroblock. Compared to the multi-view video coding with fixed quantization parameter, the proposed scheme efficiently controls the bit rate with an average rate control error of 0.6%.