In order to achieve high practical security, Natural Steganography (NS) uses cover images captured at ISO sensitivity ISO1 and generates stego images mimicking ISO sensitivity ISO2 > ISO1. This is achieved by adding a stego signal to the cover that mimics the sensor photonic noise. This paper proposes an embedding mechanism to perform NS in the JPEG domain after linear developments by explicitly computing the correlations between DCT coefficients before quantization. In order to compute the covariance matrix of the photonic noise in the DCT domain, we first develop the matrix representation of demosaicking, luminance averaging, pixel section, and 2D-DCT. A detailed analysis of the resulting covariance matrix is done in order to explain the origins of the correlations between the coefficients of 3 × 3 DCT blocks. An embedding scheme is then presented that takes into account all the correlations. It employs 4 sub-lattices and 64 lattices per sub-lattices. The modification probabilities of each DCT coefficient are then derived by computing conditional probabilities computed from a multivariate Gaussian distribution using the Cholesky decomposition of the covariance matrix. This derivation is also used to compute the embedding capacity of each image. Using a specific database called E1Base, we show that in the JPEG domain NS (J-Cov-NS) enables to achieve high capacity (more than 2 bits per non-zero AC DCT) and with high practical security (PE 40% using DCTR and PE 32% using SRNet) from QF 75 to QF 100).

中文翻译：

---

具有线性开发流程的 JPEG 领域自然隐写术


为了实现较高的实用安全性，自然隐写术 (NS) 使用在 ISO 灵敏度 ISO1 下捕获的封面图像，并生成模仿 ISO 灵敏度 ISO2 > ISO1 的隐写图像。这是通过在盖子上添加模拟传感器光子噪声的隐写信号来实现的。本文提出了一种嵌入机制，通过在量化之前显式计算 DCT 系数之间的相关性，在线性展开后在 JPEG 域中执行 NS。为了计算 DCT 域中光子噪声的协方差矩阵，我们首先开发去马赛克、亮度平均、像素部分和 2D-​​DCT 的矩阵表示。对所得协方差矩阵进行了详细分析，以解释 3 × 3 DCT 块系数之间相关性的起源。然后提出考虑所有相关性的嵌入方案。它采用 4 个子格，每个子格有 64 个格。然后通过使用协方差矩阵的 Cholesky 分解从多元高斯分布计算条件概率来导出每个 DCT 系数的修改概率。该推导还用于计算每个图像的嵌入容量。使用名为 E1Base 的特定数据库，我们表明在 JPEG 域 NS (J-Cov-NS) 中能够实现高容量（每个非零 AC DCT 超过 2 位）并具有高实际安全性（使用 DCTR 的 PE 40%）使用 SRNet 的 PE 32%）从 QF 75 到 QF 100）。