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AuthorAshref Lawgaly
AuthorFouad Khelifi
AuthorAhmed Bouridane
AuthorSomaya Al-maadeed
AuthorYounes Akbari
Available date2023-02-23T09:13:04Z
Publication Date2022
Publication NameACM International Conference Proceeding Series
ResourceScopus
URIhttp://dx.doi.org/10.1145/3529399.3529420
URIhttp://hdl.handle.net/10576/40340
AbstractThe field of digital image and video forensics has recently seen significant advances and has attracted attention from a growing number of researchers given the availability of imaging functionalities in most current multimedia devices at no cost including smartphones and tablets. Photo response non-uniformity (PRNU) noise is a sensor pattern noise characterizing the imaging device. However, estimating the PRNU from smartphone videos can be a challenging process because of the lossy compression that digital videos normally undergo for various reasons in addition to other non-unique noise components that interfere with the video data. This paper presents a new filtering technique for PRNU estimation based on the three-dimensional discrete wavelet transform followed by a 3D wiener filter. The rationale is that the 3D filter can filter out the compression artifacts along the temporal dimension in a more effective way than simple averaging. Experimental results on a public video dataset captured by various smartphone devices have shown a significant gain obtained with the proposed approach over the well-known two-dimensional wavelet-based Wiener approach.
SponsorThis work was supported by NPRP grant # NPRP12S-0312-190332 from the Qatar National Research Fund (a member of the Qatar Foundation). The statements made herein are solely the responsibility of the authors.
Languageen
PublisherAssociation for Computing Machinery
Subject3D Wavelets and Wiener Filter
Photo Response Non-Uniformity Noise
Source Smartphone Identification
TitleThree Dimensional Denoising Filter for Effective Source Smartphone Video Identification and Verification
TypeConference Paper
Pagination124-130


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