Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures <s> Decoder <s> Practically all known good constructive coding techniques for bandlimited channels, including lattice codes and various trellis-coded modulation schemes, can be characterized as coset codes. A coset code is defined by a lattice partition Lambda / Lambda ' and by a binary encoder C that selects a sequence of cosets of the lattice Lambda '. The fundamental coding gain of a coset code, as well as other important parameters such as the error coefficient, the decoding complexity, and the constellation expansion factor, are purely geometric parameters determined by C Lambda / Lambda '. The known types of coset codes, as well as a number of new classes that systematize and generalize known codes, are classified and compared in terms of these parameters. > <s> BIB001 </s> Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures <s> Decoder <s> In current interframe video compression systems, the encoder performs predictive coding to exploit the similarities of successive frames. The Wyner-Ziv Theorem on source coding with side information available only at the decoder suggests that an asymmetric video codec, where individual frames are encoded separately, but decoded ::: conditionally (given temporally adjacent frames) could achieve similar efficiency. We propose a transformdomain Wyner-Ziv coding scheme for motion video that uses intraframe encoding, but interframe decoding. In this system, the transform coefficients of a Wyner-Ziv frame are encoded independently using a scalar quantizer and turbo coder. The decoder uses previously reconstructed frames to generate side information to conditionally decode the Wyner-Ziv frames. Simulation results show significant gains above DCT-based intraframe coding and improvements over the pixel-domain Wyner-Ziv video coder. <s> BIB002 </s> Distributed video coding for wireless video sensor networks: a review of the state-of-the-art architectures <s> Decoder <s> This paper describes a hybrid coder/decoder rate control for a Wyner-Ziv video coding scheme with a feedback channel. The approach is first based on a method to estimate at the encoder the minimum rate required for the Slepian-Wolf (SW) encoded data. This estimation makes use only of the Lapacian correlation model. The decoder then estimates the bit error rate (BER) for each decoded bit plane from likelihood ratios computed at the output of the SW decoder. The robustness of the BER estimation is further improved by the use of an error detection mechanism based on a cyclic redundancy checksum. Experimental results show that rate-distortion performances are comparable to those which would be obtained by computing the Hamming distance between the original and the decoded data. In addition the hybrid coder/decoder rate control reduces the decoding complexity as well as the usage of the return channel. <s> BIB003
Syndrome decoding The syndrome bits of a sequence received at decoder are aligned according to trellis channel code to generate the quantized codeword sequence. Thereafter, the decoder employs Viterbi algorithm BIB001 to determine the closest predictor sequence among the set of predictor sequences. Motion search and CRC calculation While performing motion search on decoded syndrome bits, the decoder looks up the entire set of predictors for the best match and compares the bit sequence with the corresponding CRC check sequence, and marks it as a successful reconstruction if an exact match occurs between the two. Motion estimation, reconstruction and post processing The quantized codeword sequence together with the predictor is used for the reconstruction (transform coefficients) of the source sequence. The PRISM framework can adopt any of the reconstruction algorithms from spatio-temporal correlation interpolation to efficient extrapolation algorithms. De-quantizer and inverse transformation Following the reconstruction of the transform coefficients of the predicted source signal, de-quantization and inverse DCT transformation is performed to extract pixel values of the block. Frame interpolation model and side information generation Temporal interpolation between two successive key frames is performed to generate side information for the current frame to be decoded. However, the decoder design is flexible enough to adopt various interpolation techniques, ranging from simple average interpolation to complex symmetric motion vector (SVM) based motion compensation, which may include multiple frame predictors and intelligent segmentation features. The interpolation technique simply averages the pixel values of successive key frames to predict the pixel value of the non-key frame in between them at the corresponding location. However, SVM interpolates the motion based on the assumption that the motion vector remains the same between the successive key frames. Therefore, the block matching is performed between the successive key frames in order to estimate the symmetric motion vector for the given block of the sandwiched non-key frame. Next, the decoder performs statistical correlation between the frame to be decoded and the corresponding side information which is required for the conditional estimation of a given frame in the reconstruction module. Reconstruction Each pixel of the frame can be reconstructed provided that its decoded bitstream and side information are available at the decoder. Since symbols are grouped together in cosets associated with the levels of quantisation, therefore if the side information is close enough to the reconstructed signal resulting from the decoded bitstream, it may fall within one of the coset's bins. Alternatively, the reconstruction process relies only on the signal to be reconstructed, quantizes it to the bin boundaries and ignores the side information. Such scenarios may happen when there are high motion frames and various occlusions in place. The turbo decoder accompanied by the side information (SI 2i ) and the received parity bits generates an estimation of the quantized symbols (q) which produces an estimate (u ′ ) of the original pixel (u) for the given frame (f 2i ) using the following reconstruction function: where v, b l and b u represents the pixel in SI 2i , upper, and lower boundaries of quantization bins indexed by 2 M = q levels of quantization, respectively. The above expression states that if a pixel values lies within the quantization index boundaries, then u′ extracts its value from v, otherwise it chooses one of the boundary values near v. The decoder processes the video frames according to the GOP configuration and operates conventional intra decoder and WZ decoder in parallel for the reconstruction of key frames, and WZ frames respectively. However, in BIB002 ), the GOP size was set to 2, which implies that every alternate frame is a key frame. In later versions (e.g. BIB003  , the decoder was extended to support GOP sizes of 4, 8 and 16 frames. Conventional intra-frame decoder and frame interpolation/extrapolation Key frame decoding is relatively straight forward, since it only exploits the spatial correlation in the given frame. However, the reconstructed key frame also provides an estimate for the WZ frame to be decoded. Frame interpolation/extrapolation is performed on each decoded current key frame along with previously reconstructed frames to produce the side information W ∼ required for reconstructing the WZ frames. DCT transformation On receiving side information W ∼ , block-based DCT is performed and the resulting transformed coefficients are aligned to form coefficient bands X ∼ k , which is an estimate of each decoded bitplane of the received WZ frame X k .