@article {970,
	title = {Improving PRNU Compression Through Preprocessing, Quantization, and Coding},
	journal = {IEEE Transactions on Information Forensics and Security},
	volume = {14},
	year = {2019},
	month = {03/2019},
	pages = {13},
	chapter = {608},
	author = {L. Bondi and P. Bestagini and Fernando P{\'e}rez-Gonz{\'a}lez and S. Tubaro}
}
@conference {932,
	title = {Design of projection matrices for PRNU compression},
	booktitle = {2017 IEEE Workshop on Information Forensics and Security (WIFS)},
	year = {2017},
	month = {Dec},
	pages = {1-6},
	keywords = {acquisition time, cameras, computational complexity, data compression, defacto standard, design methodology, digital photo, forensics investigators, image coding, Image forensics, image sensors, image source identification, interpolation, matrix algebra, nearly-flat spectral characteristics, Performance evaluation, photo response nonuniformity, PRNU compression, probability, projection matrices, public image dataset, Signal to noise ratio, silicon sensor imperfections, specific camera sensor, weak multiplicative noise},
	doi = {10.1109/WIFS.2017.8267652},
	author = {L. Bondi and Fernando P{\'e}rez-Gonz{\'a}lez and P. Bestagini and S. Tubaro}
}
