Rethinking deinterlacing for early interlaced videos

TL;DR

This paper introduces a novel deinterlacing network designed to effectively remove complex artifacts from early interlaced videos, improving visual quality by addressing limitations of traditional methods.

Contribution

The paper proposes a specialized deinterlacing network with two stages, enhancing artifact removal in early interlaced videos beyond traditional approaches.

Findings

Effective removal of complex artifacts in early interlaced videos

Outperforms traditional deinterlacing methods in artifact suppression

Improves visual perception of reconstructed videos

Abstract

With the rapid development of image restoration techniques, high-definition reconstruction of early videos has achieved impressive results. However, there are few studies about the interlacing artifacts that often appear in early videos and significantly affect visual perception. Traditional deinterlacing approaches are mainly focused on early interlacing scanning systems and thus cannot handle the complex and complicated artifacts in real-world early interlaced videos. Hence, this paper proposes a specific deinterlacing network (DIN), which is motivated by the traditional deinterlacing strategy. The proposed DIN consists of two stages, i.e., a cooperative vertical interpolation stage for split fields, and a merging stage that is applied to perceive movements and remove ghost artifacts. Experimental results demonstrate that the proposed method can effectively remove complex artifacts in early interlaced videos.