Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures <s> Distributed coding for video services (DISCOVER) <s> In this paper we generalize (to nondiscrete sources) the results of a previous paper (Wyner and Ziv, 1976) on source coding with a fidelity criterion in a situation where the decoder (but not the encoder) has access to side information about the source. We define R *( d ) as the minimum rate (in the usual Shannon sense) required for encoding the source at a distortion level about d . The main result is the characterization of R *( d ) by an information theoretic minimization. In a special case in which the source and the side information are jointly Gaussian, it is shown that R *( d ) is equal to the rate which would be required if the encoder (as well as the decoder) is informed of the side information. <s> BIB001 </s> Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures <s> Distributed coding for video services (DISCOVER) <s> Wyner-Ziv (WZ) video coding ? a particular case of distributed video coding (DVC) ? is a new video coding paradigm based on two major Information Theory results: the Slepian-Wolf and Wyner-Ziv theorems. Recently, practical WZ video coding solutions were proposed with promising results. Most of the solutions available in the literature, model the correlation noise between the original frame and the so-called side information by a given distribution whose relevant parameters are estimated in an offline process, at the encoder. In this paper, three algorithms are proposed towards a more realistic WZ coding approach by performing online estimation of the error distribution at the decoder. Both algorithms explore temporal correlation between frames however with different levels of granularity: frame, block and pixel levels; better rate-distortion (RD) performance is achieved for lower granularity (pixel) level. <s> BIB002
DISCOVER (2005) is an European video coding project, which has introduced several new modules and improved existing modules to enhance the overall performance of the TDWZ codec. Notably: 1. Adaptive GOP selection and encoder rate-control mechanisms with input from decoder's virtual channel are introduced; 2. Turbo coder is replaced by LDPC coder  ); 3. Correlation noise modeling is performed between the side information and corresponding WZ frame via soft input computation to enhance the reconstruction quality. The architecture of DISCOVER is shown in Fig. 10 . Blocks 1-3 represent the encoding phase, which splits the incoming video sequence into two parts for encoding as key frames and WZ frames, using conventional encoder, and WZ encoder, respectively. Blocks 4-8 represent the decoding phase, which decodes the key frames and generates side information from which coefficients of WZ frames are estimated and then applied for decoding the WZ frames. If decoding fails, further information (e.g. more parity bits) may be requested by the decoder from the encoder through a feedback channel illustrated by the dotted line. This repeats until decoding is successful and the final video is reconstructed by multiplexing the decoded key frames and WZ frames. The following further elaborates on the aforementioned key enhancements. The selection of GOP size is made adaptive to varying temporal correlation in the video sequence . By analyzing the video frames, larger or smaller GOP size can be employed for sequences having higher, or lower temporal correlation among frames, respectively. A hierarchical clustering algorithm executed at the encoder to group frames of similar motion activity, is responsible for making the decision about the GOP size. It is observed that the codec exhibits better rate-distortion performance when such adaptive GOP is employed as compared to using fixed GOP. The LDPC channel codes introduced in  ) have replaced the turbo channel codes not only in DISCOVER, but almost all TDWZ architectures. The LDPC encoder is comprised of syndrome generator and the accumulator which stores the syndrome bits generated from LDPC codes to form the accumulated syndromes for transmission to the decoder. In contrast to turbo codes, LDPC codes efficiently utilize the capacity of channels under varying communication requirements. Furthermore, a CRC sum of the encoded bit-plane is transmitted to the decoder to perform error checking of its received bits. The rate-distortion approach proposed in BIB001 ) is used to develop the rate-control module at the encoder. It computes the minimum rate employed by the source for a given distortion measure, and enables the encoder to determine the minimum number of accumulated syndrome bits to be transmitted per bitplane for each coefficient band. This enables the DISCOVER to exhibit comparable rate-distortion performance with conventional H.264 Intra codecs. To model the correlation noise between the transform bands of WZ frame and corresponding side information, DISCOVER uses the Laplacian error distribution (Girod et al. 2005; BIB002 , which considers the variance in noise statistics pertinent to spatial and temporal correlation and evaluates the distribution parameter online. The resulting noise correlation model aids in transforming the side information's transform coefficients into soft-input for the LDPC decoder.