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Improved autoregressive image model estimation for directional image interpolation

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4 Author(s)
Xiong, Ruiqin ; Sch. of Electron. Eng. & Comput. Sci., Peking Univ., Beijing, China ; Wenpeng Ding ; Ma, Siwei ; Wen Gao

For image interpolation algorithms employing autoregressive models, a mechanism is required to estimate the model parameters piecewisely and accurately so that local structures of image can be exploited efficiently. This paper proposes a new strategy for better estimating the model. Different from conventional schemes which build the model solely upon the co-variance matrix of low-resolution image, the proposed strategy utilizes the covariance matrix of high-resolution image itself, with missing pixels properly initialized. To make the estimation robust, we adopt a general solution which exploits the covariance matrices of both scales. Experimental results demonstrate that the proposed strategy improves model estimation and the interpolation performance remarkably.

Published in:

Picture Coding Symposium (PCS), 2010

Date of Conference:

8-10 Dec. 2010

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