EIGHT ADJACENT REGRESSION BASED IMAGE INTERPOLATION FOR HR IMAGES

with bitmap graphics, as the size of an image is enlarged, the pixels that form the image become increasingly visible, making the image appear "soft" if pixels are averaged, or jagged if not. Image interpolation methods however, often suffer from high computational costs and unnatural texture interpolation. Image interpolation, which is based on an autoregressive model, has achieved significant improvements compared with the traditional algorithm with respect to image reconstruction, including a better peak signal-to-noise ratio (PSNR) and improved subjective visual quality of the reconstructed image. However, the time-consuming computation involved has become a bottleneck in those autoregressive algorithms. The main purpose of this work is to provide recursive algorithms for the computation of the Newton interpolation polynomial of a given two-variable function

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