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    Three Dimensional Denoising Filter for Effective Source Smartphone Video Identification and Verification

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    3529399.3529420.pdf (810.0Kb)
    Date
    2022
    Author
    Ashref Lawgaly
    Fouad Khelifi
    Ahmed Bouridane
    Somaya Al-maadeed
    Younes Akbari
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    Abstract
    The 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.
    DOI/handle
    http://dx.doi.org/10.1145/3529399.3529420
    http://hdl.handle.net/10576/40340
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    • Computer Science & Engineering [‎2428‎ items ]

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