A No-Reference Quality Metric for Parameter Tuning of Edge-Aware Filters – An Anti-Image Forensic Method - 22/05/21
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Abstract |
Edge-Aware Filters (EAF) are less frequently detected by forensic tools compared to the median filter. However, EAFs also blur the edges, if their operational parameters are not tuned properly. Objective image quality metrics which reflect the quality of the smoothed images are necessary for tuning the operational parameters. A novel formulation of a no-reference composite metric, termed as Denoising Performance Metric (DPM) is introduced in this paper. DPM exhibited a correlation of 0.98 ± 0.02 and 0.89 ± 0.09 with the Mean Opinion Score (MOS) and Peak Signal to Noise Ratio (PSNR) between the test images and the noise-free benchmark image, respectively. The correlation observed for type-2 Vector Mean Squared Error (VMSE) with MOS and PSNR are 0.97 ± 0.02 and 0.79 ± 0.25, respectively. The proposed metric is observed to be superior to type-2 Vector Mean Squared Error (VMSE) in terms of its correlation with the subjective fidelity ratings. It can be used for tuning operational parameters of EAF to enhance their ability to tackle forensic tools.
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Highlights |
• | A no-reference IQA Index termed as ‘Denoising Performance Metric’ is introduced. |
• | Objective parameter tuning of edge-aware filters avoids blur at the edges. |
• | Enhance ability of edge-aware filters to tackle forensic tools. |
• | Computationally simple framework. |
Keywords : Anti-image forensics, Counter-image forensics, Digital image forensics, Edge-aware filters
Plan
Vol 42 - N° 3
P. 165-173 - juin 2021 Retour au numéro
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