Video Sensor Technology For Emergency Service And Its Application

Distributed compressive video sensing is one of the most critical technologies in the video sensor system for emergency service.According to the special needs of this system,the sampling algorithm and reconstruction algorithm are investigated and applied to the video sensor system for emergency service.Firstly,in order to solve the problems of too many sampling times and excessive energy consumption in the encoder,an adaptive sampling algorithm based on temporal correlativity is proposed.The measurement rate of each block of non-key frame is allocated according to the ratio of the information of each block to that of pictures group.Then,the measurement rate of each block is calculated according to the mode of blocks.The experiment results show that the proposed algorithm provides better reconstruction quality when the measurement rates are same.The energy saving caused by the reduction of measurement times is far more than the additional energy consumption.Secondly,aiming at the problem of uneven video reconstruction in the video system,an adaptive reconstruction algorithm based on temporal correlativity is proposed.On the basis of the model of distributed compressive video sensing without feedback channel,each block of non-key frames is mode-discriminated,and the residuals between the non-key frames and their previous frames are encoded and transmitted.When the frames are reconstructed,the reconstruction modes are adaptively selected according to the result of mode discrimination to avoid the unnecessary calculation of side information.The simulation results show that the qualities of video are improved with less running time in this algorithm.Finally,according to the application scenarios of video sensor system for emergency service,the proposed adaptive sampling algorithm and reconstruction algorithm are combined in this system.Therefore,the performance of the system is improved and the system becomes more stable and fast.The simulation results show that the PSNR of the reconstructed frames of this system is higher than other systems,and the reconstruction time is significantly lower than the other two systems.This video system achieves both high system efficiency and high reconstruction quality at the same time.