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Apple's Synthetic Defocus Noise Pattern: Characterization and Forensic Applications

Apple's Synthetic Defocus Noise Pattern: Characterization and Forensic Applications

来源:Arxiv_logoArxiv
英文摘要

iPhone portrait-mode images contain a distinctive pattern in out-of-focus regions simulating the bokeh effect, which we term Apple's Synthetic Defocus Noise Pattern (SDNP). If overlooked, this pattern can interfere with blind forensic analyses, especially PRNU-based camera source verification, as noted in earlier works. Since Apple's SDNP remains underexplored, we provide a detailed characterization, proposing a method for its precise estimation, modeling its dependence on scene brightness, ISO settings, and other factors. Leveraging this characterization, we explore forensic applications of the SDNP, including traceability of portrait-mode images across iPhone models and iOS versions in open-set scenarios, assessing its robustness under post-processing. Furthermore, we show that masking SDNP-affected regions in PRNU-based camera source verification significantly reduces false positives, overcoming a critical limitation in camera attribution, and improving state-of-the-art techniques.

David Vázquez-Padín、Fernando Pérez-González、Pablo Pérez-Miguélez

计算技术、计算机技术

David Vázquez-Padín,Fernando Pérez-González,Pablo Pérez-Miguélez.Apple's Synthetic Defocus Noise Pattern: Characterization and Forensic Applications[EB/OL].(2025-05-12)[2025-06-24].https://arxiv.org/abs/2505.07380.点此复制

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