Multimedia Security, Volume 1. William Puech
ON FIGURE 1.16.– The forged image comes from the database associated with Huh et al. (2018). The Siamese network gives a similarity score for each patch with a reference patch. The black areas in the Siamese network result correspond to patches that are incompatible with the reference patch.
1.9. References
Agarwal, S. and Farid, H. (2017). Photo forensics from JPEG dimples. In Workshop on Information Forensics and Security. IEEE, Rennes.
Aguerrebere, C., Delon, J., Gousseau, Y., Musé, P. (2013). Study of the digital camera acquisition process and statistical modeling of the sensor raw data. Technical report [Online]. Available at: https://hal.archives-ouvertes.fr/hal-00733538.
Arias, P., Facciolo, G., Caselles, V., Sapiro, G. (2011). A variational framework for exemplar-based image inpainting. International Journal of Computer Vision, 93(3), 319–347.
Bammey, Q., Grompone von Giol, R., Morel, J.-M. (2020). An adaptive neural network for unsupervised mosaic consistency analysis in image forensics. In Conference on Computer Vision and Pattern Recognition (CVPR). IEEE.
Bianchi, T., De Rosa, A., Piva, A. (2011). Improved DCT coefficient analysis for forgery localization in JPEG images. In International Conference on Acoustics, Speech and Signal Processing. IEEE, Prague.
Bracho, R. and Sanderson, A. (1985). Segmentation of images based on intensity gradient information. Proc. IEEE Computer Society Conference on Computer Vision and Pattern Recognition. IEEE Computer Society Press, Amsterdam.
Buades, A., Coll, B., Morel, J.-M., Sbert, C. (2011). Self-similarity driven demosaicking. Image Processing On Line, 1, 51–56.
Chen, Y.-L. and Hsu, C.-T. (2008). Image tampering detection by blocking periodicity analysis in JPEG compressed images. In 10th Workshop on Multimedia Signal Processing. IEEE, Cairns.
Chen, M., Fridrich, J., Goljan, M., Lukáš, J. (2008). Determining image origin and integrity using sensor noise. IEEE Transactions on Information Forensics and Security, 3(1), 74–90.
Choi, C.-H., Choi, J.-H., Lee, H.-K. (2011). CFA pattern identification of digital cameras using intermediate value counting. In Multimedia Workshop on Multimedia and Security. ACM, New York.
Christlein, V., Riess, C., Jordan, J., Riess, C., Angelopoulou, E. (2012). An evaluation of popular copy–move forgery detection approaches. IEEE Transactions on Information Forensics and Security, 7(6), 1841–1854.
Clarke, R.J. (ed.) (1985). Transform coding of images. Astrophysics. Academic Press, London and Orlando, FL.
Colom, M. (2014). Multiscale noise estimation and removal for digital images. PhD Thesis, University of the Balearic Islands, Palma.
Colom, M. and Buades, A. (2013). Analysis and extension of the Ponomarenko et al. method, estimating a noise curve from a single image. Image Processing On Line, 3, 173–197.
Colom, M., Buades, A., Morel, J.-M. (2014). Nonparametric noise estimation method for raw images. Journal of the Optical Society of America A, 31(4), 863–871.
Cozzolino, D. and Verdoliva, L. (2020). Noiseprint: A CNN-based camera model fingerprint. IEEE Transactions on Information Forensics and Security, 15, 144–159.
Cozzolino, D., Poggi, G., Verdoliva, L. (2015a). Efficient dense-field copy–move forgery detection. IEEE Transactions on Information Forensics and Security, 10(11), 2284–2297.
Cozzolino, D., Poggi, G., Verdoliva, L. (2015b). Splicebuster: A new blind image splicing detector. In 2015 IEEE International Workshop on Information Forensics and Security. IEEE, Rome.
Desolneux, A., Moisan, L., Morel, J.-M. (2008). From Gestalt Theory to Image Analysis. Springer, New York.
Donoho, D.L. and Johnstone, I.M. (1994). Ideal spatial adaptation by wavelet shrinkage. Biometrika, 81(3), 425–455.
Donoho, D.L. and Johnstone, I.M. (1995). Adapting to unknown smoothness via wavelet shrinkage. Journal of the American Statistical Association, 90(432), 1200–1224.
Ehret, T. (2019). Robust copy-move forgery detection by false alarms control [Online]. Available at: https://arxiv.org/abs/1906.00649.
Ehret, T. and Facciolo, G. (2019). A study of two CNN demosaicking algorithms. Image Processing On Line, 9, 220–230.
Fan, Z. and de Queiroz, R.L. (2003). Identification of bitmap compression history: Jpeg detection and quantizer estimation. IEEE Transactions on Image Processing, 12(2), 230–235.
Fechner, G. (1860). Elemente der Psychophysik. Breitkopf and Hàrtel, Leipzig.
Fridrich, J., Goljan, M., Du, R. (2001). Steganalysis based on JPEG compatibility. Multimedia Systems and Applications IV, 4518, 275–281.
Getreuer, P. (2011). Zhang-Wu directional LMMSE image demosaicking. Image Processing On Line, 1, 117–126.
Gharbi, M., Chaurasia, G., Paris, S., Durand, F. (2016). Deep joint demosaicking and denoising. ACM Trans. Graph., 35(6), 191:1–191:12.
Ghosh, A., Zhong, Z., Boult, T.E., Singh, M. (2019). Spliceradar: A learned method for blind image forensics. In Conference on Computer Vision and Pattern Recognition Workshops. IEEE, Long Beach.
Gloe, T. (2012). Feature-based forensic camera model identification. In Transactions on Data Hiding and Multimedia Security VIII, Shi, Y.Q. (ed.). Springer, Berlin, Heidelberg.
González Fernández, E., Sandoval Orozco, A., García Villalba, L., Hernandez-Castro, J. (2018). Digital image tamper detection technique based on spectrum analysis of cfa artifacts. Sensors, 18(9), 2804.
Hamilton Jr, J.F. and Adams Jr, J.E. (1997). Adaptive color plan interpolation in single sensor color electronic camera. Document, US Patent, 5,629,734.
Huh, M., Liu, A., Owens, A., Efros, A.A. (2018). Fighting fake news: Image splice detection via learned self-consistency. In European Conference on Computer Vision. ECCV, Munich.
Iakovidou, C., Zampoglou, M., Papadopoulos, S., Kompatsiaris, Y. (2018). Contentaware detection of JPEG grid inconsistencies for intuitive image forensics. Journal of Visual Communication and Image Representation, 54, 155–170.
Immerkær, J. (1996). Fast noise variance estimation. Computer Vision and Image Understanding, 64(2), 300–302.
Kirchner, M. (2010). Efficient estimation of CFA pattern configuration in digital camera images. In Media Forensics and Security Conference. IS&T, San Jose.
Lebrun, M., Colom, M., Morel, J.-M. (2013). Secrets of image denoising cuisine. Image Processing On Line, 2013, 173–197.
Lebrun, M., Colom, M., Morel, J. (2015). Multiscale image blind denoising. IEEE Transactions on Image Processing, 24(10), 3149–3161.
Lee, J.-S. (1981). Refined filtering of image noise using local statistics. Computer Graphics and Image Processing, 15(4), 380–389.
Lee, J.-S. and Hoppel, K. (1989). Noise modeling and estimation of remotely-sensed images. In 12th Canadian Symposium on Remote Sensing Geoscience and Remote Sensing Symposium. IEEE, Vancouver.
Li, W., Yuan, Y., Yu, N. (2009). Passive detection of doctored JPEG image via block artifact grid extraction. Signal Processing, 89(9), 1821–1829.
Lin, W., Tjoa, S., Zhao, H., Ray Liu, K. (2009). Digital image source coder forensics via intrinsic fingerprints. IEEE Transactions on Information Forensics and Security, 4(3), 460–475.
Liu, C., Freeman, W.T., Szeliski, R., Kang, S.B. (2006). Noise