Prefilter design for forensic resampling estimation
Starting from a theoretical analysis of the resampling estimation problem for image tampering detection, this work presents a study, based on cyclostationarity theory, about the use of prefilters to improve the estimation accuracy of the resampling factor. Considering the methods that perform the estimation by analyzing the spectrum of the covariance of a resampled region, we propose an analytical framework that allows the definition of a cost function that measures the degree of detectability of the spectral peaks. Based on this measure, the design of the optimum prefilters for a particular resampling factor can be solved numerically. Experimental results validate the developed analysis and illustrate the enhancement of the performance in a real scenario.