This paper considers using BCH codes for distributed source coding using feedback. The focus is on coding using short block lengths for a binary source, X, having a high correlation between each symbol to be coded and a side information, Y , such that the marginal probability of each symbol, X i in X, given Y is highly skewed. In the analysis, noiseless feedback and noiseless communication are assumed. A rate-adaptive BCH code is presented and applied to distributed source coding. Simulation results for a fixed error probability show that rate-adaptive BCH achieves better performance than LDPCA (LowDensity Parity-Check Accumulate) codes for high correlation between source symbols and the side information.

Distributed video coding (DVC) is a coding paradigm which exploits the redundancy of the source (video) at the decoder side, as opposed to predictive coding, where the encoder leverages the redundancy. To exploit the correlation between views, multiview predictive video codecs require the encoder to have the various views available simultaneously. However, in multiview DVC (M-DVC), the decoder can still exploit the redundancy between views, avoiding the need for inter-camera communication. The key element of every DVC decoder is the side information (SI), which can be generated by leveraging intra-view or inter-view redundancy for multiview video data. In this paper, a novel learning-based fusion technique is proposed, which is able to robustly fuse an inter-view SI and an intra-view (temporal) SI. An inter-view SI generation method capable of identifying occluded areas is proposed and is coupled with a robust fusion system able to improve the quality of the fused SI along the decoding process through a learning process using already decoded data. We shall here take the approach to fuse the estimated distributions of the SIs as opposed to a conventional fusion algorithm based on the fusion of pixel values. The proposed solution is able to achieve gains up to 0.9 dB in Bjøntegaard difference when compared with the best-performing (in a RD sense) single SI DVC decoder, chosen as the best of an inter-view and a temporal SI-based decoder one.

Depth map coding plays a crucial role in 3D Video communication systems based on the "Multi-view Video plus Depth" representation as view synthesis performance is strongly affected by the accuracy of depth information, especially at edges in the depth map image. In this paper an efficient algorithm for edge-preserving intra depth compression based on H.264/AVC is presented. The proposed method introduces a new Intra mode specifically targeted to depth macroblocks with arbitrarily shaped edges, which are typically not efficiently represented by DCT. Edge macroblocks are partitioned into two regions each approximated by a flat surface. Edge information is encoded by means of contextcoding with an adaptive template. As a novel element, the proposed method allows exploiting the edge structure of previously encoded edge macroblocks during the context-coding step to further increase compression performance. Experiments show that the proposed Intra mode can improve view synthesis performance: average Bjøntegaard bit rate savings of 25% have been reported over a standard H.264/AVC Intra coder.Index Terms-Block-based depth compression, contextcoding, edge-based depth representation, video-plus-depth, depth-image-based-rendering.

We consider Distributed Video Coding (DVC) in presence of communication errors. First, we present DVC side information generation based on a new method of optical flow driven frame interpolation, where a highly optimized TV-L 1 algorithm is used for the flow calculations and combine three flows. Thereafter methods for exploiting the error-correcting capabilities of the LDPCA code in DVC are investigated. The proposed frame interpolation includes a symmetric flow constraint to the standard forward-backward frame interpolation scheme, which improves quality and handling of large motion. The three flows are combined in one solution. The proposed frame interpolation method consistently outperforms an overlapped block motion compensation scheme and a previous TV-L 1 optical flow frame interpolation method with an average PSNR improvement of 1.3 dB and 2.3 dB respectively. For a GOP size of 2, an average bitrate saving of more than 40% is achieved compared to DISCOVER on Wyner-Ziv frames. In addition we also exploit and investigate the internal error-correcting capabilities of the LDPCA code in order to make it more robust to errors. We investigate how to achieve this goal by only modifying the decoding. One of approaches is to use bit flipping; alternatively one can modify the parity check matrix of the LDPCA. Different schemes known from LDPC codes are considered and evaluated in the LDPCA setting. Results show that the performance depend heavily on the type of channel used and on the quality of the Side Information.

Distributed Video Coding (DVC) is a video coding paradigm allowing a shift of complexity from the encoder to the decoder. Depth maps are images enabling the calculation of the distance of an object from the camera, which can be used in multiview coding in order to generate virtual views, but also in single view coding for motion detection or image segmentation. In this work, we address the problem of depth map video DVC encoding in a single-view scenario. We exploit the motion of the corresponding texture video which is highly correlated with the depth maps. In order to extract the motion information, a block-based and an optical flow-based methods are employed. Finally we fuse the proposed Side Informations using a multi-hypothesis DVC decoder, which allows us to exploit the strengths of all the proposed methods at the same time.