Estimating JPEG compression history of bitmaps based on factor histogram

Abstract

Estimation of JPEG compression history for bitmaps has drawn increasing attention in the past decade due to its extensive applications in image processing, image forensics and steganalysis. In this paper, we propose a novel statistic named factor histogram for estimating the JPEG compression history of bitmaps. In a statistical sense, the factor histogram decreases with the increase of its bin index for uncompressed bitmaps. Whereas, it exhibits a local maximum at the bin index corresponding to the quantization step for JPEG decompressed bitmaps, which makes itself no longer decrease. Based on these characteristics, we propose to identify decompressed bitmaps by measuring the monotonicity of factor histogram, and to estimate the quantization step of each frequency by locating the bin index of the local maximum in factor histogram. Experimental results demonstrate that the proposed method outperforms the existing methods for a range of image sizes, meanwhile maintaining low computational cost.