Image filter identification using demosaicing residual features

Image filters have become a popular feature of photo editing software and camera phones. Filter identification can provide useful information for us to determine source and processing history of images. Currently, there is no forensic work done to perform filter identification. In this paper, we propose a framework to search for color correlations left by different filters in a set of interpolation residuals obtained from various demosaicing algorithms. To effectively capture the structures of color correlations, we design a diverse set of geometric co-occurrence patterns and gather both intra-channel and inter-channel color dependencies using co-occurrence matrices. Experiments conducted on two large image databases full demonstrate the ability of our framework to identify a wide range of filters provided by both cameras and third-party software.