Forgery Detection via Inter-channel Correlation of CFA Images
Xiaoli Zhang · 2015
Most digital cameras use a single sensor to capture only one component among the three colors(RGB) for each pixel, together with a color filter array(CFA) interpolating the other two after data acquisition. In this work, spectral correlation introduced by inter-channel CFA interpolation is exploited to realize image authentication. By analyzing differences in the frequency spectrum between inter-channel interpolated images and the natural ones, we extract forensics features from the high frequency areas of the green-red spectral difference. After re-interpolating the test image, we detect tampered images according to changes in the forensic features. Experimental results demonstrate effectiveness in forgery detection and robustness to JPEG compression.