First quantization matrix estimation for double compressed JPEG images utilizing novel DCT histogram selection strategy

The Double JPEG problem in image forensics has been gaining importance since it involves two compression cycles and there is a possibility of tampering having taken place after the first cycle thereby calling for accurate methods to detect and localize the introduced tamper. First quantization matrix estimation which basically retrieves the missing quantization table of the first cycle is one of the ways of image authentication for Double JPEG images. This paper presents a robust method for first quantization matrix estimation in case of double compressed JPEG images by improving the selection strategy which chooses the quantization estimate from the filtered DCT histograms. The selection strategy is made robust by increasing the available statistics utilizing the DCT coefficients from the double compressed image under investigation coupled with performing relative comparison between the obtained histograms followed by a novel priority assignment and selection step, which accurately estimates the first quantization value. Experimental testing and comparative analysis with two state-of-art methods show the robustness of the proposed method for accurate first quantization estimation. The proposed method finds its application in image forensics as well as in steganalysis.