Abstract
In the digital heritage field, the accurate reproduction of hard-to-photograph items, such as daguerreotypes, ambrotypes, and tintypes, is an ongoing challenge. Industrial contactless sensors offer the potential to improve the quality of scanned images, but their capabilities and limitations have not been fully explored. In our research, a dataset of 48 scans was created using the hi-tech industrial contactless sensor CRUSE. Moreover, 3 rare original photographs were scanned in 16 different modes, the most suitable images were determined by specialists in the restoration, and validated through experiments involving eye-tracking, multiple computer vision, and image processing methods. Our study identified the Cruse scanning modes, which can be utilized to achieve the most accurate digital representation of scanned originals. Secondly, we proposed several methods for highlighting the degradation and minor scratches on photographs that otherwise might not be detected by the restorer's naked eye. Our findings belong to four overlapping areas, i.e., image understanding, digital heritage, information visualization, and industrial sensors research. We publish the entire dataset under the CC BY-NC 4.0 license. The CRUSE sensor shows promise as a tool for improving the quality of scanned images of difficult-to-photograph items. Further research is necessary to fully understand its capabilities and limitations in this context.