Block-level adaptive optimization for inter-layer texture up-sampling in H.264/SVC

Kan Chang, Tuanfa Qin, Wenhao Zhang, Aidong Men
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Abstract

H.264 Scalable Video Coding (SVC) extension has spatial scalability which is able to provide various resolution sequences for a single encoded bit-stream. In order to reduce redundancies between different layers, for spatial scalable intra-coded frames, co-located reconstructed 8×8 sub-macroblock in base layer (BL) is up-sampled to predict the marcoblock (MB) in enhancement layer (EL). Unfortunately, simple 1-D poly-phase up-sampling filter used in current SVC isn't cable of achieving ideal result, which limits the performance of inter-layer intra prediction (ILIP). This paper proposes an adaptive optimization method for inter-layer texture up-sampling by applying wiener filter and controlling it at block level. Working as an additional part of ILIP, the proposed method can greatly reduce the prediction error between the original EL signals and the up-sampled BL signals. Experimental results show that, the proposed method achieves bit rate reduction up to 14.25% and PSNR increment up to 0.97 dB when compared with the traditional method in current SVC.
H.264/SVC帧间纹理上采样的块级自适应优化
H.264可扩展视频编码(SVC)扩展具有空间可扩展性,能够为单个编码的比特流提供各种分辨率序列。为了减少不同层之间的冗余,对于空间可扩展的编码内帧,对基层(BL)中重构的8×8子宏块进行上采样,以预测增强层(EL)中的宏块(MB)。遗憾的是,目前SVC中使用的简单的一维多相上采样滤波器并不能达到理想的效果,这限制了层间内预测(ILIP)的性能。提出了一种基于维纳滤波的层间纹理上采样自适应优化方法。作为ILIP的附加部分,该方法可以大大降低原始EL信号与上采样BL信号之间的预测误差。实验结果表明,与现有的SVC方法相比,该方法的比特率降低了14.25%,PSNR增加了0.97 dB。
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