The quality of digital content has become increasingly significant in digital broadcasting systems. These days, consumers react to even subtle defects in media content, which, in turn, influence consumer satisfaction about the content. The development of digital broadcasting technology has replaced tape-based content with file-based content. Nonetheless, in the process of generating file-based content, people are often confronted with different types of errors. Detecting such errors and fixing them require a substantial amount of time and human labor, whereas being unable to fix them might lead to broadcast failure. Therefore, in this paper, we introduce an automated restoration system that reduces intensive human labor in fixing errors in the content generating process. Our automated video restoration system can be applied to different types of classic errors. We developed several customized algorithms to restore each error in the digital content derived from the Korean Broadcasting System video archives. Implementing our method as a familiar tool for content producers is also a consideration. We are developing the restoration system as a plug-in to a well-known nonlinear editing system.
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