最新的视频编码技术H.264/AVC及可伸缩性扩展视频编码(Scalable Video Coding,SVC)通过多模式预测的方法实现了极高的压缩效率,同时也明显提升了编码复杂度。为减少SVC HighIntra Profile中增强层帧内编码模式选择的计算复杂度,本文提出一种快速的帧内模式选择算法:通过对增强层少量帧的编码模式进行全搜索,确定增强层中各种编码模式的分布情况以及增强层与底层的纹理相关性,然后利用模式分布的统计结果,直接跳过出现概率很低的预测模式;同时,本算法利用层间相关性的统计结果,通过查表的形式,省去增强层部分低效预测方向的模式选择过程。实验结果表明,在几乎不影响率失真性能的前提下,本算法能节约50%以上的编码时间。
In this paper,a distributed compressive spectrum sensing scheme in wideband cognitive radio networks is investigated.An analog-to-information converters（AIC） RF front-end sampling structure is proposed which use parallel low rate analog to digital conversions（ADCs） and fewer storage units for wideband spectrum signal sampling.The proposed scheme uses multiple low rate congitive radios（CRs） collecting compressed samples through AICs distritbutedly and recover the signal spectrum jointly.A general joint sparsity model is defined in this scenario,along with a universal recovery algorithm based on simultaneous orthogonal matching pursuit（S-OMP）.Numerical simulations show this algorithm outperforms current existing algorithms under this model and works competently under other existing models.
