We propose the first accurate digitization and color reconstruction process for historical lenticular film that is robust to artifacts. Lenticular films emerged in the 1920s and were one of the first technologies that permitted to capture full color information in motion. The technology leverages an RGB filter and cylindrical lenticules embossed on the film surface to encode the color in the horizontal spatial dimension of the image. To project the pictures the encoding process was reversed using an appropriate analog device. In this work, we introduce an automated, fully digital pipeline to process the scan of lenticular films and colorize the image. Our method merges deep learning with a model-based approach in order to maximize the performance while making sure that the reconstructed colored images truthfully match the encoded color information. Our model employs different strategies to achieve an effective color reconstruction, in particular (i) we use data augmentation to create a robust lenticule segmentation network, (ii) we fit the lenticules raster prediction to obtain a precise vectorial lenticule localization, and (iii) we train a colorization network that predicts interpolation coefficients in order to obtain a truthful colorization. We validate the proposed method on a lenticular film dataset and compare it to other approaches. Since no colored groundtruth is available as reference, we conduct a user study to validate our method in a subjective manner. The results of the study show that the proposed method is largely preferred with respect to other existing and baseline methods.
翻译:我们为历史扁豆胶片提出了第一个精确的数字化和色彩重建程序,该程序对文物具有很强的功能。 Lesterical电影于1920年代出现,是最早允许在运动中捕捉全彩信息的技术之一。该技术利用电影表面的 RGB 过滤器和圆柱状扁豆胶囊,将图像水平空间维度的颜色编码。要用一个适当的模拟设备来预测编码过程的反向图象。在这项工作中,我们引入了一个自动的、完全数字化的管道,处理对扁豆胶囊的扫描和图像的色彩化。我们的方法将深层学习与基于模型的方法相结合,以便最大限度地提高性能,同时确保已重建的彩色图像真实地与已编码的彩色信息匹配。我们的模型采用不同的战略来有效地进行彩色重建,特别是(一)我们使用数据扩增能力来创建一个强大的扁豆分解网络。 (二)我们更倾向于让扁豆浆的预测,以获得准确的矢量缩本地化,以及(三)我们用一个彩色化的参考网络来训练一个彩色化的深度学习,以便预测现有的用户行为方法。我们用另一种方法来验证。我们用比较了另一种方法后,我们用另一种方法来比较。我们用另一种方法来研究。我们用现有的方法来验证。我们用另一种方法是为了比较。我们用另一种方法来研究。我们用另一种方法来研究。