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The quality of digital content has become increasingly significant in the digitalized broadcasting world. These days, consumers react even to subtle defects in media content, which in turn, influence consumer satisfaction about the entire 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 requires a substantial amount of time and human labor, while 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 the errors in the content generation process. Our automated video restoration system can be applied to different types of classical errors. We developed several algorithms to restore each error in the digital content derived from the KBS video archive. Implementing our method using a tool already familiar to content producers has also been one of our considerations. We are developing the restoration system as a plug-in to a well-known NLE (Non-linear editing system).