Research On Video Compressed And Traffic Model In Wireless Multimedia Network

Recently,with the rapid development of economy and construction of communication network infrastructure,people are not satisfied with the traditional sounds and words transmission based on the single media such as telephone,TV,fax and email.Data,graphics,images,audio and video information are needed to be showed as a whole,in which video with abundant information takes an important part in the field of multimedia communications.However,the factors directly influence QoS of video service and are important parts in multimedia communication,which are how to implement efficient compression of video source in the condition of meeting HVS, transmit video signal in the wireless channel environment,and provide prediction model based on video traffic properties for design of multimedia network.The work of this dissertation is supported by the National Natural Science Foundation of China "Study of New Traffic Stream Models and Fuzzy Evolutionary Neural Network/Ant Algorithm Based Resource Management Technologies in Wireless Multimedia Networks(No.60472034)","Study of Joint Channel Rate-Distortion Model in Wireless Broadband Network(No.60772042)",and the project of China Aerospace Science & Industry Corp.which is "Sensor Images Telemetry Device".The dissertation studies on the problems of video coding,which include smoothing motion estimation, adaptive quantization based on human visual system,and joint source channel coding in wireless networks.And then in order to implement admission control and optimal bandwidth allocation of video traffic,the prediction model and traffic properties are analyzed.The main innovations in the thesis are outlined as following:On the Basis of the existing search methods of motion vector,the novel hybrid pattern search(HPS) method is proposed.And then according to the Kalman filter, Rate-Distortion theory and the candidate motion vectors which are obtained by the HPS method,a smooth rate-distortion optimal motion estimation algorithm is presented.The result of true motion field can be obtained by the smoothing filtering and cost function.Simulations on computational efficiency,accuracy and motion distribution show that this algorithm can capture motion of target effectively.In order to balance the coding information and distortion by adjusting quantization parameter,the relationship between target bit rate and quantization parameter is analyzed.We have studied the approximate quadratic relationship between bit rate differenceΔR and adjusting factors of quantization parameterΔQ,and proposed the iterative process for calculating quantization parameter adjusting factor which is the necessary factor of implementing adaptive quantization based on HVS.With respect to non-uniformity characteristic of the results of video image activity normalization,analyzing the relationship of normalized factors and characteristics of video image,an improved activity normalization method is proposed.Meanwhile, by discussing performances of HVS and according to the true motion field got in chapterⅡ,the following are studied respectively:the relationship of luminance and spatial activity,the relationship of motions and temporal activity,the correlation among the interframes and the corresponding error distribution.A novel method of error distribution feedback quantization scheme based on HVS is proposed. Simulation results show that the objective and subjective quality has been improved at the expense of less complexity by adopting adaptive quantization based on HVS.We have studied the structure of video transmission system,and presented a new method of source distortion estimation based on SDDCT and model of channel distortion for Intra-/Inter-frame based on performances analysis of source distortion and residual distortion in BSC channel.Meanwhile,the source rate model is proposed according to the statistical analysis of source coding.Finally,based on the rate model and distortion model,we have presented a scheme of joint source channel coding.Compared with independent coding,the results of PSNR show that quality of reconstructing video by joint coding is better than by non-joint coding about 2dB.We have analyzed the properties of video traffic and presented a wavelet on-line prediction model based on linear correlation structure of scaling space and wavelet space in MPEG trace.The proposed algorithm of error feedback adaptive linear prediction is given by LRD of scale coefficients of traffic;meanwhile the linear correlation structure is used by SRD of wavelet coefficients of traffic.Finally,the prediction traffic is obtained by inversion wavelet.It is verified by the simulations that this prediction model can capture the probability distribution and LRD of the traffic very well because of modeling scale space and wavelet space respectively.