An effective method for blind detection of image splicing with nonsubsampled contourlet transform and image quality evaluation

Nonsubsampled contourlet transform (NSCT) has multi-resolution, location, anisotropy, translation invariance and other characteristics. Sections 1 and 2 of the full paper explain the method of detection mentioned in the tide. Their core consists of; (1) we utilize the statistical properties of an image and its quality evaluation to extract its features, thus capturing the differences between original image and fake image; (2) for the statistical properties, we use image blocks to obtain the coefficient matrices with the NSCT; we evaluate the image quality with the block effects. Section 3 uses the support vector machine to train and test the image splicing. The test results, given in Tables 1 and 2, and their analysis show preliminarily that, compared with other detection methods, our detection method can indeed effectively reduce the number of dimensions of the statistical properties and the computational complexity.