Image Interpolation by Adaptive 2-D Autoregressive Modeling

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.