@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} }