The excellent cover estimation is very important to the payload location of JPEG image steganography. But it is still hard to exactly estimate the quantized DCT coefficients in cover JPEG image. Therefore, this paper proposes a JPEG image steganography payload location method based on optimal estimation of cover co-frequency sub-image, which estimates the cover JPEG image based on the Markov model of co-frequency sub-image. The proposed method combines the coefficients of the same position in each 8 × 8 block in the JPEG image to obtain 64 co-frequency sub-images and then uses the maximum a posterior (MAP) probability algorithm to find the optimal estimations of cover co-frequency sub-images by the Markov model. Then, the residual of each DCT coefficient is obtained by computing the absolute difference between it and the estimated cover version of it, and the average residual over coefficients in the same position of multiple stego images embedded along the same path is used to estimate the stego position. The experimental results show that the proposed payload location method can significantly improve the locating accuracy of the stego positions in low frequencies.

出色的覆盖估计对于JPEG图像隐写术的有效负载位置非常重要。但是，仍然很难精确估计封面JPEG图像中的量化DCT系数。因此，本文提出了一种基于覆盖同频子图像的最优估计的JPEG图像隐写有效载荷定位方法，该方法基于同频子图像的马尔可夫模型来估计覆盖JPEG图像。所提出的方法结合了JPEG图像中每个8×8块中相同位置的系数，以获得64个同频子图像，然后使用最大后验（MAP）概率算法来找到覆盖co-马尔可夫模型的频率子图像 然后，通过计算DCT系数与其估计的覆盖版本之间的绝对差来获得每个DCT系数的残差，并使用沿着相同路径嵌入的多个Stego图像的相同位置的平均剩余系数系数来估计Stego位置。实验结果表明，提出的有效载荷定位方法可以显着提高低频下隐身位置的定位精度。