Title :
Rate-distortion analysis of weighted prediction for error resilience
Author :
Liu, Yuxin Zoe ; Kurceren, Ragip ; Mukherjee, Debargha
Author_Institution :
Hewlett-Packard Labs., Palo Alto, CA
Abstract :
In this paper, we extend our work in [1] and address an approach to theoretically analyze the rate-distortion (R-D) performance of the weighted prediction feature provided within the scope of H.264/AVC. We consider the weighted prediction as a standard-compatible leaky prediction approach for the purpose of error resilience. We adopt a quantization noise model that explicitly formulates the relationship between the data rate and the distortion in the mean-square-error (MSE) sense. We derive a comprehensive rate-distortion function for both the error- free scenario and the one with error drift. Through adjusting the weight coefficients in H.264/AVC, we also simulate H.264/AVC video streaming over error-prone networks and obtain the operational rate-distortion results using various leaky factors for both error-free and error- drift scenarios. We compare our theoretical results with the operational R-D curves and demonstrate that the theoretical results conform with the operational results.
Keywords :
mean square error methods; quantisation (signal); rate distortion theory; video coding; video streaming; H.264/AVC; error resilience; mean-square-error; quantization noise model; rate-distortion analysis; standard-compatible leaky prediction approach; video streaming; weighted prediction; Automatic voltage control; Filters; Motion compensation; Performance analysis; Quantization; Rate distortion theory; Rate-distortion; Resilience; Streaming media; Video codecs; H.264/AVC; Leaky prediction; error resilience; rate distortion; video compression;
Conference_Titel :
Image Processing, 2008. ICIP 2008. 15th IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-1765-0
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2008.4712184