This study investigates the different aspects of multimedia computing in Video Synthetic Aperture Radar(Video-SAR)as a new mode of radar imaging for real-time remote sensing and surveillance.This research also conside...This study investigates the different aspects of multimedia computing in Video Synthetic Aperture Radar(Video-SAR)as a new mode of radar imaging for real-time remote sensing and surveillance.This research also considers new suggestions in the systematic design,research taxonomy,and future trends of radar data processing.Despite the conventional modes of SAR imaging,Video-SAR can generate video sequences to obtain online monitoring and green surveillance throughout the day and night(regardless of light sources)in all weathers.First,an introduction to Video-SAR is presented.Then,some specific properties of this imaging mode are reviewed.Particularly,this research covers one of the most important aspects of the Video-SAR systems,namely,the systematic design requirements,and also some new types of visual distortions which are different from the distortions,artifacts and noises observed in the conventional imaging radar.In addition,some topics on the general features and high-performance computing of Video-SAR towards radar communications through Unmanned Aerial Vehicle(UAV)platforms,Internet of Multimedia Things(IoMT),Video-SAR data processing issues,and real-world applications are investigated.展开更多
文摘视频合成孔径雷达(video synthetic aperture radar,VideoSAR)的超长相干孔径观测使得区域动态信息的快速浏览极其困难。为以机器视觉方式自动捕捉地物散射消失-瞬态持续-消失-瞬态持续-消失的关键帧变化全过程,提出了一种子孔径能量梯度(subaperture energy gradient,SEG)和低秩与稀疏分解(low-rank plus sparse decomposition,LRSD)相结合的VideoSAR关键帧提取器。提取器为系列性通用架构,适用于任何SEG和LRSD系列方法相结合的形式。所提技术首要针对同时单通道、单波段、单航迹等有限信息条件的解决途径,有助于打破应急响应场景中难以采集多通道、多波段、多航迹或多传感器数据的应用局限性。基于实测数据处理和多种先进LRSD算法进行了对比验证,其代表性散射信息的充分提取可促进未来快速地理解并浓缩区域动态。
文摘基于目标阴影的跟踪技术是视频合成孔径雷达(video synthetic aperture radar,ViSAR)目标探测的重要手段,但ViSAR数据存在目标特征不明显且随时间不规则变化、相干斑噪声干扰强等问题,使得ViSAR目标阴影跟踪精度较低。为此,提出了一种鲁棒的基于时间信息加权的ViSAR目标阴影跟踪算法。针对目标特征不明显且随时间不规则变化的问题,将尺度自适应均值偏移(adaptive scale mean shift,ASMS)跟踪算法引入到ViSAR目标阴影跟踪中,同时在ASMS算法的背景比例加权(background ratio weighted,BRW)技术中添加历史帧的特征,并对尺度正则项进行时间信息加权修正,来对目标特征进行整合。针对相干斑噪声干扰强的问题,对ASMS算法加入局部中值滤波操作的预处理步骤,在不增加计算量的同时平滑了噪声。在对两类ViSAR数据集上不同尺寸、不同运动状态的目标阴影的跟踪实验结果表明,与现有高性能跟踪算法相比,所提算法在保证了实时性的基础上提高了跟踪精度,且不需要额外的训练样本,具备较好的工程应用价值。
文摘This study investigates the different aspects of multimedia computing in Video Synthetic Aperture Radar(Video-SAR)as a new mode of radar imaging for real-time remote sensing and surveillance.This research also considers new suggestions in the systematic design,research taxonomy,and future trends of radar data processing.Despite the conventional modes of SAR imaging,Video-SAR can generate video sequences to obtain online monitoring and green surveillance throughout the day and night(regardless of light sources)in all weathers.First,an introduction to Video-SAR is presented.Then,some specific properties of this imaging mode are reviewed.Particularly,this research covers one of the most important aspects of the Video-SAR systems,namely,the systematic design requirements,and also some new types of visual distortions which are different from the distortions,artifacts and noises observed in the conventional imaging radar.In addition,some topics on the general features and high-performance computing of Video-SAR towards radar communications through Unmanned Aerial Vehicle(UAV)platforms,Internet of Multimedia Things(IoMT),Video-SAR data processing issues,and real-world applications are investigated.
