Transmission distortion modeling for wireless video communication

In video transmission over wireless networks, the channel is error-prone and the compressed video data is highly sensitive to errors. The transmission errors causes decoding failure and distort the pictures. This type of picture distortion is called transmission distortion. In this work, we develop a predictive approach for transmission modeling so that the encoder is able to estimate the average transmission distortion of the decoded video data. Our simulation results demonstrate that the proposed model is robust and accurate. Using this type of predictive transmission distortion model, the encoder is able to intelligently allocate its resources, such as bits and energy, to maximize the decoded video quality at receiver side.