Hybrid DCT-Wiener-based interpolation via improved spatial filter

Resizing video frames is one of the key techniques for multimedia processing. In particular, it is more desirable to generate high-resolution video frames from low-resolution sources to meet the needs of customers with larger screen displays and higher display requirement. The original hybrid DCT-Wiener-based interpolation scheme provides a powerful framework to interpolate video frames by combining the information in both spatial and DCT domain seamlessly. It can provide both better objective and visual qualities with low complexity than existing interpolation methods. This paper presents an enhancement over the original hybrid scheme to further improve its performance. We first analyze the bottleneck of the original hybrid interpolation scheme, and then propose a novel spatial interpolation scheme to further improve its performance. The spatial interpolation scheme designed in this research is a contour-enhanced Wiener filter with unsharp masking post-processing. It is learnt using training video frame pairs through the minimum mean square error estimation, which is able to resolve the quarter-pixel shift issue and achieve much better performance over the original 1-D 6-tap pixel-based Wiener filter. Experiments have been carried out to demonstrate that the proposed scheme achieves noticeable gains over the original hybrid interpolation scheme as well as other existing schemes in both objective and visual qualities.