BlueNeg: A 35mm Negative Film Dataset for Restoring Channel-Heterogeneous Deterioration

While digitally acquired photographs have been dominating since around 2000, there remains a huge amount of legacy photographs being acquired by optical cameras and are stored in the form of negative films. In this paper, we focus on the unique phenomenon of deterioration on negative films and propose the first high-quality 35mm negative film dataset BlueNeg for restoring channel-heterogeneous deterioration. We would like to bring attention to this under-explored research area of image restoration on channel-heterogeneous deterioration. However, a large portion of the collected negative films are already contaminated, so we do not have non-corrupted version or the ground truth of these photos, which poses a challenge in evaluating the restoration performance. To address this, we leverage the printed photos from the same negative films, which do not suffer from the channel-heterogeneous deterioration, for quantitative evaluation. We propose a reverse-developing process to generate the estimated ground truth from the printed photos and design an evaluation protocol for evaluating the restoration performance. With the collected data and the proposed evaluation protocol, we find existing image restoration methods cannot perform well on our dataset, requiring specially designed tools for better restoration. We hope that our dataset and benchmark will inspire future research in this area, especially in the context of legacy photograph restoration for preserving historical moments and archival purposes. Our dataset will be publicly available at HuggingFace Hub under a derivative license based on CC-BY.