A 3D auto-regressive model for bidirectional prediction

Yongbing Zhang; Debin Zhao; Siwei Ma; Ronggang Wang; Wen Gao

doi:10.1117/12.805698

19 January 2009 A 3D auto-regressive model for bidirectional prediction

Yongbing Zhang, Debin Zhao, Siwei Ma, Ronggang Wang, Wen Gao

Proceedings Volume 7257, Visual Communications and Image Processing 2009; 72571I (2009) https://doi.org/10.1117/12.805698
Event: IS&T/SPIE Electronic Imaging, 2009, San Jose, California, United States

Abstract

In this paper, a 3D auto-regressive (AR) model is proposed for bi-directional prediction. The prediction is composed of two 3D AR models, which are along the forward and backward directions, respectively. Applying the 3D AR model, each pixel in the current frame is predicted as a weighted summation of pixels within a spatial neighborhood along the forward/backward motions within the forward/backward reference frames. Ultimately, the prediction of each pixel is obtained as the combination of predictions generated by the two 3D AR models. To derive accurate AR coefficients, this paper proposes a framework that performs simultaneous coefficient estimation and image interpolation. As opposed to other methods, the predicted pixels generated by one 3D AR model are further used to predict the pixels in adjacent frame along the motion trajectory. Consequently, each pixel in one forward/backward reference frame can be predicted as a nonlinear combination of pixels within an enlarged spatial neighborhood along the motion in one backward/forward reference frame. An iterative algorithm using a nonlinear least squares method is then devised to compute the optimum 3D AR coefficients. Various experiments conducted in this paper have confirmed that the proposed method has superior performance for bi-directional prediction.

Citation Download Citation

Yongbing Zhang, Debin Zhao, Siwei Ma, Ronggang Wang, and Wen Gao "A 3D auto-regressive model for bidirectional prediction", Proc. SPIE 7257, Visual Communications and Image Processing 2009, 72571I (19 January 2009); https://doi.org/10.1117/12.805698

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