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Proceedings Paper

Image interpolation by adaptive 2-D autoregressive modeling
Author(s): Vinit Jakhetiya; Ashok Kumar; Anil Kumar Tiwari
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Paper Abstract

This paper presents a new interpolation algorithm based on the adaptive 2-D autoregressive modeling. The algorithm uses a piece-wise autoregressive (PAR) model to predict the unknown pixels of high resolution image. For this purpose, we used a block-based prediction model to predict the unknown pixels. The unknown pixels are categorized into three categories and they are predicted using predictors of different structure and order. Prediction accuracy and the visual quality of the interpolated image depend on the size of the window. We experimentally found an appropriate window size and have shown that subjective as well as objective (PSNR) quality of the high resolution (HR) images is same, on an average, as that of the competitive such method reported in literature and also the method is a single pass.

Paper Details

Date Published: 26 February 2010
PDF: 6 pages
Proc. SPIE 7546, Second International Conference on Digital Image Processing, 75461J (26 February 2010); doi: 10.1117/12.855785
Show Author Affiliations
Vinit Jakhetiya, The LNM Institute of Information Technology (India)
Ashok Kumar, The LNM Institute of Information Technology (India)
Anil Kumar Tiwari, The LNM Institute of Information Technology (India)


Published in SPIE Proceedings Vol. 7546:
Second International Conference on Digital Image Processing
Kamaruzaman Jusoff; Yi Xie, Editor(s)

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