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Conventional video coding approaches follow a hybrid motion prediction / residual transform coding paradigm, which limits the discovery of redundancy to individual pairs of video frames.
On the other hand, computer vision techniques like structure-from-motion (SfM) have long exploited redundancy across a large group of frames to estimate a rigid 3D object structure.
In this paper, leveraging on previous SfM techniques, we construct a rate-distortion (RD) optimized 3D planar model from a target spatial region in a frame group as a unified signal predictor for these frames.

In this work we study the 4D sparsity of light fields using as main tool the 4D-Discrete Cosine Transform. We analyze the two JPEG Pleno light field datasets, namely the lenslet-based and the High- Density Camera Array (HDCA) datasets. The results suggest that the lenslets datasets exhibit a high 4D redundancy, with a larger inter-view sparsity than the intra-view one. For the HDCA datasets, there is also 4D redundancy worthy to be exploited, yet in a smaller degree. Unlike the lenslets case, the intra-view redundancy is much larger than the inter-view one.

This work presents a thresholding method for processing the predicted samples in the state-of-the-art High Efficiency Video Coding (HEVC) standard. The method applies an integer-based approximation of the discrete cosine transform to an extended prediction block and sets transform coefficients beneath a certain threshold to zero. Transforming back into the sample domain yields the improved prediction signal. The method is incorporated into a software implementation that is conforming to the HEVC standard and applies to both intra and inter predictions.

HEVC is the latest block-based video compression standard, outperforming H.264/AVC by 50% bitrate savings for the same perceptual quality. An HEVC encoder provides Rate-Distortion optimization coding tools for block-wise compression. Because of complexity limitations, Rate-Distortion Optimization (RDO) is usually performed independently for each block, assuming coding efficiency losses to be negligible.

In this paper, residual redundancy in compressed videos is exploited to alleviate transmission errors using joint source channel arithmetic decoding. A new method is proposed to estimate a priori probability in MAP metric of H.264 intra modes decoder. The decoder generates a decoding tree using a breadth first search algorithm. An introduced statistical model is then implemented stage by stage over the decoding tree.