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In this paper, we present an efficient side information extrapolation scheme with temporal and spatial consistency for low-delay Wyner-Ziv video coding. Our method is based on the regularized local linear regression (RLLR) model, in which each pixel in SI is approximated as a linear weighted combination of samples within a local temporal neighborhood. The optimal model parameters are estimated by...
Approaches to image compression and indexing based on extensions to 2D of some of the Lempel-Ziv incremental parsing techniques have been proposed in the recent past. In these approaches, an image is decomposed into a number of patches, consisting each of a square or rectangular solid block. This paper proposes image compression techniques based on patches that are not necessarily solid blocks, but...
The unique requirements imposed by contemporary video communication applications promote the rise of the distributed video coding paradigm, which offers flexible complexity allocation and error resilience combined with competitive compression performance. This work proposes a novel Wyner-Ziv video coding scheme, performing hash-based motion estimation at the decoder. Subsequently, maximum likelihood...
Self-similarity is an attractive image property which has recently found its way into object recognition in the form of local self-similarity descriptors. In this paper we explore global self-similarity (GSS) and its advantages over local self-similarity (LSS). We make three contributions: (a) we propose computationally efficient algorithms to extract GSS descriptors for classification. These capture...
In this paper, we propose Blind Source Separation (BSS) methods for possibly-correlated images, based on a low sparsity assumption. To satisfy this sparsity condition, one of the versions of our methods applies a wavelet transform to the observed images before performing separation. Another version directly operates in the original spatial domain, when the sources are sparse enough in this domain...
The coding efficiency of distributed video coding system is significantly determined by the side information quality and correlation model. Motivated by theoretical analysis of the maximum likelihood treatment for linear regression model, we propose a novel joint online learning model for side information generation and correlation model estimation in this paper. In our proposed scheme, each pixel...
Most of the Wyner-Ziv (WZ) video coding schemes in literature model the correlation noise (CN) between original frame and side information (SI) by a given distribution whose parameters are estimated in an offline process. In this paper, an online CN modeling algorithm is proposed towards a more practical WZ-based error resilient video coding (WZ-ERVC). In ERVC scenario, the side-information is typically...
Present distributed video coding (DVC) approaches assume the correlation channel to be side-information independent (SII). We have recently demonstrated that in reality the correlation channel in video is side-information dependent (SID) and that DVC systems which make SII assumptions suffer a significant performance penalty, depending entirely on the correlation statistics of the video data. In this...
This paper proposes a multi-hypothesis based Wyner-Ziv (WZ) decoder for the multi-view distributed video coding (MDVC). Two hypotheses, the intra-view SI and the interview SI, are fed together into the WZ decoder in the proposed scheme. A multi-hypothesis based correlation model (MHBCM) is presented to fully exploit the redundancy between these two SI frames and the original frame. The MHBCM is also...
The paper addresses an essential problem in distributed video coding (DVC) which is modeling and estimation of the correlation channel. Current works assume the distribution of the correlation noise to be independent from the realization of the side-information. The paper demonstrates that this assumption is inaccurate and proposes a novel model which depends on the realization of the side-information...
Current models in Wyner-Ziv video coding consider the temporal correlation noise to be side-information independent (SII). This paper goes beyond this assumption and proposes a novel model, of which the parameters are side-information dependent (SID). The proposed model is experimentally validated showing remarkable accuracy improvement over the conventional SII model. Moreover, a novel SID technique...
A number of properties of separable covariance matrices are summarized. Expressions for the divergence of the corresponding two-dimensional Gaussian random processes are given in terms of row and column covariance matrices, and in terms of linear prediction parameters and maximum likelihood spectral estimates. Such time and frequency domain expressions are not widely known, even for one-dimensional...
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