A Framework For Parameters Estimation Of Image Operator Chain

Currently, many effective techniques have been proposed to estimate the parameters of tampering operations. Most of them consider the situation that an image is tampered by only one operation. However, multiple manipulation operations are always used to tamper an image in our daily life. Moreover, since the tampering traces of previous operations may be weakened or eliminated by later ones, the detecting accuracy of methods used for detecting single operations would be reduced. In this paper, we propose a new method to estimate the parameters of operations in different manipulation chains. Especially, we first investigate the correlation of operations and divide the degree of interactions between them into uncoupled and coupled. Furthermore, resizing and median filtering are adopted to reveal the assessment framework. Meanwhile, we propose well-directed features including energy density of difference-image to estimate operation parameters. The experiment proves the effectiveness of our method.