Blind CFA Interpolation Detection Based on Covariance Matrix

Blind CFA interpolation detection, which identifies the demosaicing method used in digital camera by analyzing output images, provides an efficient tool for digital image forensics. This paper proposes an approach of blind CFA interpolation detection based on interpolation coefficients estimation. By solving the covariance matrix equation, a vector of the interpolation coefficients is obtained, which is further fed to SVM classifier. The experimental results show a high accuracy on blind CFA interpolation detection. Compared with existing ones, the proposed method in this paper indicates a better performance on the robustness against additive Gaussian white noises and lossy JPEG compression.