In contrast to conventional video coding, Wyner-Ziv video coders
perform simple intra-frame encoding and complex inter-frame decoding using
side information. An important process in Wyner-Ziv decoding
is the reconstruction process. So far, two main reconstructions have
been used: the Maximum a Posteriori (MAP) reconstruction and the Minimum
Mean Square Error (MMSE) reconstruction. In this paper, we study the
MAP and MMSE reconstructions for both Pixel-Domain and Transform-Domain
Wyner-Ziv video coders.
We also present a new reconstruction function for Pixel-Domain Wyner-Ziv video coders
that adapts to the local accuracy of the side information.
Experimental results show that our adaptive reconstruction provides
improvements over both the MAP and the MMSE reconstructions.
Wyner-Ziv video coders perform simple intra-frame encoding and complex inter-frame decoding. This feature makes this type of coder suitable for applications that require low-complexity encoders. Video coding algorithms provide coding modes and parameters so that encoders can fulfill rate constraints and improve the coding
efficiency. However, in most Wyner-Ziv video coders, no algorithm is used to optimally choose the coding modes and parameters. In this paper, we present a rate control algorithm for pixel-domain Wyner-Ziv video coders. Our algorithm predicts the rate and distortion of each video frame as a function of the coding mode and the quantization parameter. In this way, our algorithm can properly select the best mode and quantization for each video frame. We show experimentally that, even though the rate and distortion cannot be accurately predicted in Wyner-Ziv video encoders, rate constraints are approximately fulfilled and good coding efficiency is obtained
by using our algorithm.
Low complexity video encoding shifts the computational complexity
from the encoder to the decoder, which is developed for applications characterized by scarce resources at the encoder. Wyner-Ziv and Slepian-Wolf theorems have provided the theoretic bases for low complexity video encoding. In this paper, we propose a low complexity video encoding using B-frame direct modes. We extend the direct-mode idea that was originally developed for encoding B frames, and design new B-frame direct modes. Motion vectors are obtained for B-frames at the decoder and transmitted back to the encoder using a feedback channel, hence no motion estimation is needed at the encoder to encoding any B frame. Experimental results implemented by modifying ITU-T H.26L software show that our approach can obtain a competitive rate distortion performance compared to that of conventional high complexity video encoding.
Proc. SPIE. 5685, Image and Video Communications and Processing 2005
KEYWORDS: Distortion, Microchannel plates, Quantization, Video coding, Video, Signal to noise ratio, Electroluminescence, Computer programming, Data modeling, Error analysis
Leaky prediction layered video coding (LPLC) incorporates a scaled
version of the enhancement layer in the motion compensated prediction (MCP) loop, by using a leaky factor between 0 and 1, to
balance between coding efficiency and error resilience performance. In this paper, we address the theoretic analysis of LPLC using two different approaches: the one using rate distortion theory and the one using quantization noise modeling. In both approaches, an alternative block diagram of LPLC is first developed, which significantly simplifies the theoretic analysis. We consider two scenarios of LPLC, with and without prediction drift in the enhancement layer, and obtain two sets of rate distortion functions in closed form for both scenarios. We evaluate both closed form expressions, which are shown to conform with the operational results.
In this paper we study two rate control strategies for fully fine-grained scalable (FFGS) video coders. Usually, in scalable coders the bitstream is divided into a base layer, which is decoded by all the decoders, and one or more enhancement layers which can improve the quality provided by the base layer. In Internet video streaming it is important that the bitstream be scalable in rate, which allows a server to adapt the bitstream to changes in the available bandwidth in the network. FFGS coders allow the maximum degree of rate scalability by using scalable encoding in both the base and enhancement layers. In this paper, we propose a rate control algorithm which is based on the rate distortion characteristics of the encoded bitstream and prevents large jumps in quality. We show that due to the embedding property of FFGS encoders, we can properly select the number of bits of every layer and frame by taking into account the quality of the video sequence. In addition, by allowing a controlled amount of prediction drift, we can set the rate control of the base layer much higher and gain in some cases several dB of PSNR performance at the highest rate. Experimental comparisons are made using SAMCoW, a FFGS video coder based on the wavelet transform and motion compensated prediction, and the MPEG-4/FGS coder using the TM-5 rate control algorithm.
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