Prediction of transmission distortion for wireless video communication: Algorithm and application

In this paper, we develop algorithms for estimating transmission distortion in wireless video communication systems. By leveraging the analytical results obtained in our previous works, we design low complexity algorithms that are capable of estimating transmission distortion accurately. We also extend our algorithm for pixel-level transmission distortion estimation to pixel-level end-to-end distortion estimation. Furthermore, we apply our pixel-level end-to-end distortion estimation algorithm to prediction mode decision in H.264 encoder. Experimental results show that (1) our transmission distortion estimation algorithm is more accurate and more robust against inaccurate channel estimation than existing distortion estimation algorithms; (2) our mode decision algorithm achieves remarkable PSNR gain over the existing algorithms for prediction mode decision in H.264 encoder, e.g., an average PSNR gain of 1.44 dB for ‘foreman’ sequence when Packet Error Probability (PEP) equals 5%.

Research highlights
► Our transmission distortion estimation algorithm is more accurate and more robust against inaccurate channel estimation than existing distortion estimation algorithms.
► Our pixel-level transmission distortion estimation algorithm is with lower complexity and higher degree of extensibility than existing distortion estimation algorithms.
► Our mode decision algorithm achieves remarkable PSNR gain over the existing algorithms for prediction mode decision in H.264 encoder.