Adaptive Interpolation Filter Scheme In Av1

Video codecs heavily depend on sub-pixel level motion compensation to achieve superior compression performance. Interpolation filters with both anti-aliasing and denoising properties play a critical role in producing high quality prediction at sub-pixel positions. Prior research has developed many adaptive filtering schemes to improve the prediction precision for compression gains. On the other hand, such filtering operations require intense computation and may lead to scattered cache footprints, therefore, account for a major portion of the overall decoding cost in both software and hardware implementations. An adaptive interpolation filtering scheme is proposed in this work to optimize the trade off between prediction quality and decoding performance. It employs a separable model and selects filter kernels independently for horizontal and vertical directions to better capture statistical variations. In order to obtain sharper transition and reduce the ripple effect in the passband in frequency domain, a 12-tap filter is introduced in conjunction with a complimentary operation design that minimizes its impact on the decoding performance. The scheme achieves on average 1.3% coding gains across a wide range of test settings, with fairly limited additional hardware cost.