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arXiv · 2505.07380

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

David Vázquez-Padín·Fernando Pérez-González·Pablo Pérez-Miguélez
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Abstract

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.

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David Vázquez-Padín, Fernando Pérez-González, Pablo Pérez-Miguélez. 2025-05-12. Apple's Synthetic Defocus Noise Pattern: Characterization and Forensic Applications. https://doi.org/10.1109/tifs.2026.3653213

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