Intelligent Repair Method for Archival Videos Based on the Super-SloMo Technology

Abstract

Abstract Due to equipment limitations in the early shooting of video files, and the damage and aging in the later file storage process, some historic video materials in video archives can easily suffer from defects such as poor action coherence. This paper proposes an intelligent enhanced repair method for archival videos. The method first obtains the frame rate of the input video, then calculates the dynamic coefficient of the video according to the frame rate and duration number, uses the artificial intelligence algorithm Super-SloMo technology to fix the problematic digital video to the required frame rate, improves the video's dynamic coefficient, and finally achieves the purpose of getting the enhanced repaired digital copies of the original video materials from video archives. This paper also proposes an intelligent enhanced repair prototype system based on the method. The experiment shows that the enhanced repair effect is effective and improves the clarity and coherence of the video. Users get more coherent copies of historic video materials. This solves the problem of the poor perception caused by the loss of frames, preserves the original information, and makes the information obtained from archival videos intuitive.