An SVD approach to forensic image resampling detection

This paper describes a new strategy for image resampling detection whenever the applied resampling factor is larger than one. Delving into the linear dependencies induced in an image after the application of an upsampling operation, we show that interpolated images belong to a subspace defined by the interpolation kernel. Within this framework, by computing the SVD of a given image block and a measure of its degree of saturated pixels per row/column, we derive a simple detector capable of discriminating between upsampled images and genuine images. Furthermore, the proposed detector shows remarkable results with blocks of small size and outperforms state-of-the-art methods.