ABSTRACT
Virtually all optical imaging systems introduce a variety of aberrations into an image. Chromatic aberration, for example, results from the failure of an optical system to perfectly focus light of different wavelengths. Lateral chromatic aberration manifests itself, to a first-order approximation, as an expansion/contraction of color channels with respect to one another. When tampering with an image, this aberration is often disturbed and fails to be consistent across the image. We describe a computational technique for automatically estimating lateral chromatic aberration and show its efficacy in detecting digital tampering.
- T.E. Boult and G. Wolberg. Correcting chromatic aberrations using image warping. In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, pages 684--687, 1992.Google ScholarCross Ref
- H. Farid and E. Simoncelli. Differentiation of multi-dimensional signals. IEEE Transactions on Image Processing, 13(4):496--508, 2004. Google ScholarDigital Library
- J. Fridrich, D. Soukal, and J. Lukáš. Detection of copy-move forgery in digital images. In Proceedings of DFRWS, 2003.Google Scholar
- E. Hecht. Optics. Addison-Wesley Publishing Company, Inc., 4th edition, 2002.Google Scholar
- M.K. Johnson and H. Farid. Exposing digital forgeries by detecting inconsistencies in lighting. In ACM Multimedia and Security Workshop, New York, NY, 2005. Google ScholarDigital Library
- J. Lukáš, J. Fridrich, and M. Goljan. Detecting digital image forgeries using sensor pattern noise. In Proceedings of the SPIE, volume 6072, 2006.Google Scholar
- T. Ng and S. Chang. A model for image splicing. In IEEE International Conference on Image Processing, Singapore, 2004.Google Scholar
- A.C. Popescuand, H. Farid. Exposing digital forgeries by detecting duplicated image regions. Technical Report TR2004- 15, Department of Computer Science, Dartmouth College, 2004.Google Scholar
- A.C. Popescuand, H. Farid. Exposing digital forgeries by detecting traces of resampling. IEEE Transactions on Signal Processing, 53(2):758--767, 2005. Google ScholarDigital Library
- A.C. Popescu and H. Farid. Exposing digital forgeries in color filter array interpolated images. IEEE Transactions on Signal Processing, 53(10):3948--3959, 2005. Google ScholarDigital Library
- P. Viola and W.M. Wells, III. Alignment by maximization of mutual information. International Journal of Computer Vision, 24(2):137--154, 1997. Google ScholarDigital Library
- R.G. Willson and S.A. Shafer. What is the center of the image? Journal of the Optical Society of America A, 11(11):2946--2955, November 1994.Google ScholarCross Ref
Index Terms
- Exposing digital forgeries through chromatic aberration
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