多路高清YUV视频GPU实时拼接研究

摘要

To improve the real-time performance of high-definition video stitching,a stitching method of GPU-based real-time multi-channel high-definition YUV video is proposed.Firstly,the perspective model of YUV422 image stitching is deduced,and then parallel optimization of the stitching steps including perspective warping and image blending are realized and performed on GPU by Compute Unified Device Architecture(CUDA)technology.The experimental results show that,on the condition of implementing four-channel 1080p video stitching,the method in this paper achieves 20%~40% improvement in real-time performance over RGB color model-based stitching method on different GPU,and video frame rate of 33 frame per second on GTX 780.%为提高高清视频拼接的实时性能,提出一种基于GPU的多路高清YUV视频实时拼接方法,推导出YUV422图像拼接中的透视模型,并结合计算统一设备架构技术,实现透视变换、无缝融合等关键拼接步骤在GPU上的并行优化.在4路1080p高清视频上的实验结果表明,相比基于RGB颜色模型的拼接方法,该方法的实时拼接性能在不同GPU架构上有20%~40%的提升,并且在GRX780上能达到33 frame/s的视频帧率.