视频流分片编码的无人机视频传输方法  

UAV Video Transmission Method Based on Video Stream Slicing and Coding

作　　者：李亮亮 吕志刚[1] 郭锦[1] 李晓艳[1] 杨永侠[1] Li Liangliang;Lu Zhigang;Guo Jin;Li Xiaoyan;Yang Yongxia(School of Electronics and Information Engineering,Xi'an Technological University,Xi'an,Shaanxi 710021,China)

机构地区：[1]西安工业大学电子信息工程学院,陕西西安710021

出　　处：《激光与光电子学进展》2020年第24期219-229,共11页Laser & Optoelectronics Progress

基　　金：国家自然科学基金(61671362);陕西省科技厅重点研发计划(2019GY-022);陕西省组合与智能导航重点实验室开放基金(SKLIIN-20180201);西安市未央区科技计划(201921);西安工业大学大学校长基金(XAGDXJJ17012)。

摘　　要：为了解决消费级无人机(UAV)视频图像在传输过程中出现的高时延、低可靠性等问题,提出一种适用于消费级无人机的视频传输算法。发送图像时,对视频流进行分帧分片,采用分量变换,对Y,Cr,Cb三分量进行三级离散小波正变换、位平面分解、组织编码、并行传输处理。接收过程与发送过程相逆,将接收的完整图像存入二级缓存区以进行后续处理。小波变换保证了图像传输的可靠性,图像编码减轻了图像传输的负荷,图像并发及二级缓存接收进一步提高了图像的实时性。在传输距离为20m的WIFI环境下,对分辨率为640×480、1280×720图像分别进行测试。640×480图像下,接收帧率均值为47.7frame/s,时延均值为35.7ms,结构相似性(SSIM)均值为0.984,方均根误差(RMSE)均值为1.61;1280×720图像下,指标依次为28.8frame/s、45.9ms、0.978、2.68。实验结果表明,当消费级无人机在超低空拍摄时,所提算法能够满足高清视频流实时可靠传输的要求,也可应用在其他图像传输领域。To solve the problems of high-time delay and low reliability of consumer UAV video images during the transmission process,this paper proposes a video transmission algorithm suitable for consumer UAVs.With the proposed algorithm,the frames of a received real-time video image are sliced while transmitting images.Color component transform is employed to obtain Y,Cr,and Cb components,which are processed by third-level forward discrete wavelet transformation,bit plane decomposition,image coding,and parallel transmission.Additionally,the receiving process is inversed compared to the sending process.The restored complete image is stored in second-level cache,which is performed by other functions.Wavelet transform ensures image transmission reliability,image coding reduces image transmission load,and image concurrency and secondary buffer reception improve the real-time performance of images.In a WIFI environment with a communication distance of 20m,two common images(resolutions are 640×480 and 1280×720)are tested.The former's average receiving frame ratio,time delay,structural similarity(SSIM),and root mean square error(RMSE)are 47.7frame/s,35.7ms,0.984,and 1.61,respectively,and the latter's values are 28.8frame/s,45.9ms,0.978,and 2.68,respectively.The experimental results demonstrate that when a consumer UAV is shooting at ultra-low altitude,the proposed algorithm can satisfy the real-time and reliable transmission requirements of a high-definition video stream.Additionally,the proposed algorithm can be applied to other image transmission fields.

关 键 词：图像处理 离散小波正变换 离散小波逆变换 图像二级缓存 小波逼近 高清视频传输 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术]