2004•Unpublished venueRequires access

Distortion chains for predicting the video distortion for general packet loss patterns

Jacob Chakareski, J.G. Apostolopoulos, Wai-Tian Tan, S. Wee, Bernd Girod

Open publisher page 31 citations

Abstract

When designing a system for video communication over a lossy packet network, it is highly beneficial to have a mechanism for accurately predicting the mean-squared error (MSE) distortion that results from different packet loss patterns. The paper proposes a distortion chains model for accurately predicting the end-to-end distortion for different general packet loss patterns. The performance is examined using JVT/H.264 encoded video sequences and previous frame error concealment. It is shown that, for all tested sequences, the proposed model predicts the total distortion due to a packet loss pattern within a 10% error bound 80% of the time, as compared to the conventional additive approach which achieves the same accuracy less then 40% of the time.

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What this paper is about

When designing a system for video communication over a lossy packet network, it is highly beneficial to have a mechanism for accurately predicting the mean-squared error (MSE) distortion that results from different packet loss patterns. The paper proposes a distortion chains model for accurately predicting the end-to-end distortion for different general packet loss patterns. The performance is examined using JVT/H.264 encoded video sequences and previous frame error concealment. It is shown that, for all tested sequences, the proposed model predicts the total distortion due to a packet loss pattern within a 10% error bound 80% of the time, as compared to the conventional additive approach which achieves the same accuracy less then 40% of the time.

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OpenAlex reports 31 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

When designing a system for video communication over a lossy packet network, it is highly beneficial to have a mechanism for accurately predicting the mean-squared error (MSE) distortion that results from different packet loss patterns. The paper proposes a distortion chains model for accurately predicting the end-to-end distortion for different general packet loss patterns. The performance is examined using JVT/H.264 encoded video sequences and previous frame error concealment. It is shown that, for all tested sequences, the proposed model predicts the total distortion due to a packet loss pattern within a 10% error bound 80% of the time, as compared to the conventional additive approach which achieves the same accuracy less then 40% of the time.

Key concepts: Distortion (music), Lossy compression, Packet loss, Computer science, Network packet, Algorithm, Mean squared error, Frame (networking)

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