  Early interlaced videos usually contain multiple and interlacing and complex
compression artifacts, which significantly reduce the visual quality. Although
the high-definition reconstruction technology for early videos has made great
progress in recent years, related research on deinterlacing is still lacking.
Traditional methods mainly focus on simple interlacing mechanism, and cannot
deal with the complex artifacts in real-world early videos. Recent interlaced
video reconstruction deep deinterlacing models only focus on single frame,
while neglecting important temporal information. Therefore, this paper proposes
a multiframe deinterlacing network joint enhancement network for early
interlaced videos that consists of three modules, i.e., spatial vertical
interpolation module, temporal alignment and fusion module, and final
refinement module. The proposed method can effectively remove the complex
artifacts in early videos by using temporal redundancy of multi-fields.
Experimental results demonstrate that the proposed method can recover high
quality results for both synthetic dataset and real-world early interlaced
videos.
