Error-resilient joint source-channel video coding using intra-refresh and dynamic rate-allocation based on distortion analysis in H.264 for low bitrate wireless video transmission - Dela Cruz, Angelo R.
The error resilient features of the video encoder and the error protection bits provided by the channel encoder are commonly used to reduce the effects of transmission distortion caused by the unreliable network. However, when the channel is reliable, these error control tools become unnecessary, effectively wasting the redundancy bits that could have been allocated for source coding. Note that reducing the bits allocated for source coding essentially increases the quantization distortion. This is most evident in video sequences with high motion activity. Thus, there is an inherent trade-off between the quantization distortion that is dictated by the source input and the transmission distortion dictated by the channel condition. The error control parameters of the source and channel encoders must be jointly optimized to be able to minimize the overall effect of quantization and transmission distortions. In this study, we develop a new technique where the intra-refresh rate of the video encoder and the code rate of the channel encoder are jointly optimized based on the characteristics of the source input and channel condition. We employ the intra-refresh method as the error control tool of the H.264/AVC encoder and the rate compatible punctured convolutional (RCPC) coding as the channel encoder. The intra-refresh rate and the code rate are jointly determined based on the minimum estimated end-to-end distortion. In line with this, we develop new distortion models that estimate the end-to-end distortion as functions of intra-refresh rate and code rate. The distortion models are sequence independent and based on the residual information and quantization step of the frame to be encoded. We also develop for the first time a linear model that predicts the residual information of the current frame as a function of intra-refresh rate. This allows proper selection of quantization parameter based on the intra-refresh rate. The distortion models are able to estimate accurately the actual distortion before encoding the frame at various intra-refresh rates, test sequences, bitrates, and SNR conditions. The distortion models are employed in a standard H.264/AVC reference encoder and we are able to develop three joint source-channel coding (JSCC) algorithms. The first JSCC scheme is the adaptive intra-refresh rate (AIRR) algorithm where the optimum intra-refresh rate is determined. The second is the joint source-channel rate-allocation (JSC-RA) algorithm where the proper bit allocation between source and channel encoders is obtained. The third scheme is the cross-layer error-control (CLEC) algorithm where the intra-refresh rate and code rate are jointly selected. Significant improvements of up to 7.1dB in objective quality are measured under wireless slow fading channel using various test sequences, bitrates, and SNR conditions proving the effectiveness of the distortion models. Comparisons are made using fixed code rates combined with intra-refresh tools inherent in standard H.264/AVC encoder.