We describe a method to maintain quality for video transported over wireless channels. The method is built on three fundamental blocks. First, we use a transcoder that injects spatial and temporal resilience into an encoded bitstream. The amount of resilience is tailored to the content of the video and the prevailing error conditions, as characterized by bit error rate. Second, we derive analytical models that characterize how corruption propagates in a video that is compressed using motion-compensated encoding and subjected to bit errors. Third, we use rate distortion theory to compute the optimal allocation of bit rate among spatial resilience, temporal resilience, and source rate. Furthermore, we use the analytical models to generate the resilience rate distortion functions that are used to compute the optimal resilience. The transcoder then injects this optimal resilience into the bitstream. Simulation results show that using a transcoder to optimally adjust the resilience improves video quality in the presence of errors while maintaining the same input bit rate.

We describe a method to maintain an acceptable quality for video transported over wireless networks under time-varying conditions. We use a transcoder to modify the resilience of the encoded bitstream by using source coding techniques to provide the appropriate level of resilience for the prevailing channel conditions. We develop a statistical model for image loss versus resilience and wireless conditions. Simulation results indicate that using a transcoder to adjust the resilience can improve video quality when errors occur without significantly sacrificing quality when there are no errors. Also, simulation results compare favorably to the analytical model.