A pixel-based digital photo authentication framework via demosaicking inter-pixel correlation

Demosaicked images possess spatially periodic inter-pixel correlation, because interpolation strategies at any logically equivalent spatial pixel location are identical. Taking this statistical characteristic, much research on imaging forensics has been done recently. We proposed a generalized neural network framework to simulate the stylized computational rules in demosaicking through bias and weight value adjustment. As experiments show, our framework is effective in recognizing the demosaicking algorithms for raw CFA images, as well as digital photo authentication, compared to the state-of-the-art methods.