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Review of chapter 2

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jfmcarreira
2018-07-30 15:38:33 +01:00
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042_ConcealmentAwareEncoding/ConcealmentAwareEncoding.tex
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%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
% CHAPTER
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
\chapter{Error Concealment-Aware Coding for Robust Video Transmission}
\chapter{Error Concealment-Aware for Robust Video Decoding}
\label{Chapter:ConcealmentAwareTechniques}
%\vspace{-6mm}
%\clearpage
@@ -42,7 +42,7 @@ Chapter~\ref{Chapter:ErrorResilienceReview} described different \ac{ec} algorith
In this chapter a robust coding driven by \ac{ec} methods with the objective of enhancing the quality of reconstructed video at decoders receiving erroneous streams from the transmission network. The proposed approach combines error resilience tools at the encoder-side with \ac{ec} at the decoder-side. Different approaches were proposed in the past to that address the problem of \ac{ec} at the encoder-side \cite{ConcealmentDrivenSliceOrdering2008,ConcealmentAwareME2006,ErrorResilienceModeHEVC2016}. Moreover, extra information was used to aid the \ac{ec} operation at the decoder-side, either by sending redundant data \cite{ResilienceRECAP_ICASSP2009,SaliencyErrorConcealment_TM2013} or by embedding data into the bitstream \cite{ConcealmentIntraDataHidng2009}. Although the above methods facilitate the EC performance either through slice reordering or based on \acs{mv}, they always rely on the assumption that a fixed \ac{ec} method is used at the decoder. The work presented in \cite{ConcealmentSignalling2008,SignallingRobustScalable2015} proposes testing several methods with transmission of extra symbols to indicate the best method to be applied by the decoder. Although such approaches achieves reasonably good performance, it relies on the spatial neighbouring information or multi-layer video, which may not be available in all cases.
To advance one step further, in this chapter an EC-aware encoding scheme is proposed to achieve higher flexibility in terms of the error concealment approaches which leads to higher recovered video quality.
To advance one step further, in this chapter an EC-aware encoding scheme is proposed to achieve higher flexibility in terms of the error concealment approaches which leads to higher recovered video quality.
This is accomplished by selecting at the encoder, among several \ac{ec} algorithms with different characteristics, the one that yields the lowest reconstruction distortion at the decoder and also minimises the \ac{rd} cost considering the necessary signalling rate. Thus, the proposed approach outperforms similar previous methods \cite{ConcealmentAwareME2006,ErrorResilienceModeHEVC2016} by selecting the best error concealment method without affecting the encoder optimisation.
To further improve the quality of recovered frames, an enhancement layer is encoded with the mismatch residue between the transmitted and recovered frames. This is a dynamic optimisation process, which is more efficient than traditional approaches based on redundant pictures \cite{RedudantPicsJan2009,VPxResiliencePCS2016}, which transmit the whole frame as redundancy.
In contrast with previous work presented in Chapter~\ref{Chapter:ErrorResilienceTechniques} that addressed the error resilience problem by optimising the coding dependencies, the approach followed in this work considers both \ac{ec} performance and the rate required for signalling the best \ac{ec} mode to the decoder.
042_ConcealmentAwareEncoding/Results/TableOveralPerformance.tex
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@@ -76,7 +76,7 @@ BQSquare & 35.64 & +1.47 & +1.18 & +2.01 & +1.77 \\ \hline
Four People & 39.16 & +0.47 & -0.65 & +0.40 & -0.06 \\ \hline
Kimono & 36.19 & +1.41 & -0.54 & +3.09 & +3.47 \\ \hline
Park Scene & 34.54 & +2.06 & +2.01 & +3.22 & +3.15 \\ \hline
People & 29.48 & +1.50 & +1.35 & +2.64 & +3.08 \\ \hline
People On Street & 29.48 & +1.50 & +1.35 & +2.64 & +3.08 \\ \hline
Race Horses & 29.08 & +2.34 & +4.52 & +5.35 & +6.02 \\ \hline
Tennis & 32.71 & +1.32 & +3.13 & +3.81 & +4.97 \\ \hline
\textbf{Average} & \textbf{--} & \textbf{+1.55} & \textbf{+1.88} & \textbf{+3.10} & \textbf{+3.33} \\
@@ -119,7 +119,7 @@ BQSquare & 31.36 & +2.50 & +2.40 & +3.33 & +3.55 \\ \hline
Four People & 37.12 & +1.24 & -0.99 & +1.82 & +1.51 \\ \hline
Kimono & 32.24 & +0.12 & -1.92 & -0.04 & -0.21 \\ \hline
Park Scene & 30.42 & +1.22 & +1.56 & +2.92 & +3.64 \\ \hline
People & 25.05 & +0.40 & +0.74 & +0.97 & +2.09 \\ \hline
People On Street & 25.05 & +0.40 & +0.74 & +0.97 & +2.09 \\ \hline
Race Horses & 24.19 & +0.63 & +2.53 & +2.75 & +3.74 \\ \hline
Tennis & 27.08 & +1.30 & +3.51 & +4.58 & +6.61 \\ \hline
\textbf{Average} & \textbf{--} & \textbf{+1.36} & \textbf{+1.96} & \textbf{+3.13} & \textbf{+3.79} \\