A novel image splicing detection method based on the inconsistency of image noise

Aiming at localizing tampered image regions, a novel detection method is proposed. Based on the statistical properties of image features, we expose the tampered parts by dividing image into some sub-blocks and computing the noise variance of each ones. Then we choose Laplace fitting based on the maximal likelihood estimation method to decide the boundary between tampered regions and the original. Several examples are shown to demonstrate the proposed method's output. We also demonstrate the efficiency of our method in paper.