Rate-distortion analysis of weighted prediction for error resilience | IEEE Conference Publication | IEEE Xplore

Rate-distortion analysis of weighted prediction for error resilience


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 provide...Show More

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.
Date of Conference: 12-15 October 2008
Date Added to IEEE Xplore: 12 December 2008
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Conference Location: San Diego, CA, USA

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