The current art of steganography shows that schemes using a deflection criterion (such as MiPOD) for JPEG steganography are usually subpar with respect to distortion-based schemes. We link this lack of performance to a poor estimation of the variance of the model of the noise on the cover image. However, this statistically-based method provides a better assessment of the detectability of hidden data as well as theoretical guarantees under a given model. In this paper, we propose a method to obtain better estimates of the variances of DCT coefficients by taking into account the dependencies introduced by development pipeline on pixels. A second method, which is a side-informed extension of Gaussian Embedding in the JPEG domain using quantization error as side-information, is also formulated and shown to achieve state-of-the-art performances. Eventually, the trade-off between noise and content complexity in steganography is thoroughly analyzed through the lenses of these two new methods using a wide range of numerical experiments.

中文翻译：

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基于可检测性的JPEG隐写技术对处理管道进行建模：噪声内容的权衡

当前的隐写术技术表明，对于基于失真的方案，使用偏转标准（例如MiPOD）进行JPEG隐写术的方案通常低于标准方案。我们将这种性能不足与对封面图像上噪声模型的方差估计不佳联系起来。但是，这种基于统计的方法可以更好地评估隐藏数据的可检测性，以及在给定模型下的理论保证。在本文中，我们提出了一种方法，该方法通过考虑开发流水线对像素引入的依赖性来获得更好的DCT系数方差估计。还提出了第二种方法，该方法是使用量化误差作为副信息在JPEG域中进行高斯嵌入的副信息扩展，并已显示出该方法可实现最新的性能。