@inproceedings{c983a80072c74cf59d0da58ffe909a0a,
title = "Reverse Imaging Pipeline for Raw RGB Image Augmentation",
abstract = "We propose a reverse camera imaging pipeline to convert arbitrary images to raw RGB responses of a specific camera. The pipeline requires only that the camera{\textquoteright}s RGB responses are characterized. The reversed pipeline helps camera developers to generate camera specific raw images and use them to train learning-based imaging pipeline algorithms. In our experiments, three recent deep color constancy architectures achieve superior results in the cross-dataset setting using generated images.",
keywords = "Image color analysis, Cameras, Pipelines, Pipeline processing, Lighting, Transforms, Data augmentation, imaging pipeline",
author = "Samu Koskinen and Dang Yang and Joni-Kristian K{\"a}m{\"a}r{\"a}inen",
note = "EXT={"}Koskinen, Samu{"}; IEEE International Conference on Image Processing ; Conference date: 01-01-1900",
year = "2019",
month = sep,
doi = "10.1109/ICIP.2019.8804406",
language = "English",
isbn = "978-1-5386-6250-2",
series = "IEEE International Conference on Image Processing",
publisher = "IEEE",
pages = "2896--2900",
booktitle = "2019 IEEE International Conference on Image Processing (ICIP)",
address = "United States",
}