  Compression methods based on inpainting are an evolving alternative to
classical transform-based codecs for still images. Attempts to apply these
ideas to video compression are rare, since reaching real-time performance is
very challenging. Therefore, current approaches focus on simplified
frame-by-frame reconstructions that ignore temporal redundancies. As a remedy,
we propose a highly efficient, real-time capable prediction and correction
approach that fully relies on partial differential equations (PDEs) in all
steps of the codec: Dense variational optic flow fields yield accurate
motion-compensated predictions, while homogeneous diffusion inpainting is
applied for intra prediction. To compress residuals, we introduce a new highly
efficient block-based variant of pseudodifferential inpainting. Our novel
architecture outperforms other inpainting-based video codecs in terms of both
quality and speed. For the first time in inpainting-based video compression, we
can decompress FullHD (1080p) videos in real-time with a fully CPU-based
implementation, outperforming previous approaches by roughly one order of
magnitude.
