Abstract
In this paper, we propose an adaptive interpolation scheme based on iterative back-projection and human visual system based quality metric for image sequences. Initial estimates of each up-sampled image can be generated individually by using subpixel interpolation and subpixel motion estimation in the spatial and temporal domains respectively. Then, based on the initial estimates and edge information, up-sampled images are derived by using an iterative back-projection technique and a quality metric based on the human visual system. After fusing the up-sampled images into a final version, a low-pass filter is applied as a post-processing step to reduce the effect of blocking artifacts in each reconstructed up-sampled image. Our experimental results demonstrate that, in terms of PSNR (Peak Signal-to-Noise Ratio) and NQM (Noise Quality Metric), the proposed scheme outperforms four existing methods.
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