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Plug-and-Play PRNU Enhancement Algorithm with Guided Filtering.

Yufei Liu1, Yanhui Xiao1, Huawei Tian1

  • 1School of National Security, People's Public Security University of China, Beijing 100038, China.

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Summary
This summary is machine-generated.

Photo Response Non-Uniformity (PRNU), a crucial digital image forensic marker, is often corrupted by low-frequency noise. This study identifies PRNU

Keywords:
digital imaging-device forensicguided filteringhigh-frequency enhancementphoto response non-uniformitysource camera identification

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Area of Science:

  • Digital Image Forensics
  • Signal Processing
  • Computer Vision

Background:

  • Photo Response Non-Uniformity (PRNU) is a weak high-frequency signal in digital images, vital for forensic applications.
  • Low-frequency interference significantly degrades PRNU extraction, hindering its reliability in source camera identification and image integrity verification.
  • Existing PRNU enhancement algorithms are disparate and cannot be integrated for improved performance.

Purpose of the Study:

  • To determine the effective frequency band of PRNU.
  • To develop a novel PRNU enhancement algorithm to suppress low-frequency interference.
  • To create a universally compatible enhancement module for existing PRNU techniques.

Main Methods:

  • Conducted a frequency-by-frequency analysis of estimated PRNU signals.
  • Proposed a guided-filtering PRNU enhancement algorithm utilizing PRNU components below 10 Hz as a guide.
  • Integrated the algorithm as a plug-and-play module with existing enhancement methods.

Main Results:

  • Identified the dominant PRNU frequency band to be above 10 Hz.
  • The guided-filtering algorithm effectively reconstructs and filters low-frequency interference.
  • Demonstrated significant suppression of low-frequency noise and amplification of the high-frequency PRNU signal.
  • Experimental validation on Dresden and Daxing datasets confirmed the method's efficiency and robustness.

Conclusions:

  • PRNU predominantly exists in frequencies above 10 Hz, enabling targeted noise suppression.
  • The proposed guided-filtering algorithm enhances PRNU reliability by effectively removing low-frequency interference.
  • This plug-and-play module offers a versatile solution to improve PRNU-based digital forensics in practical scenarios.