Since the inception of pixel value differencing (PVD) image steganography, it has drawn considerable interest among the researchers of this field. However, most of the PVD based techniques suffer from either falling-off boundary problem (FOBP) or incorrect extraction problem (IEP). Therefore, to address these two issues, this paper proposes a multi-directional pixel value differencing and modulus function (MDPVDMF) based technique. During the embedding process, the original image (OI) is partitioned into 2 × 2 size pixel blocks. Then, data embedding is performed by exploiting the horizontal, vertical, and diagonal directions for each block. For a 2 × 2 pixel block, two difference values can be obtained in any of the three directions. Next, using the difference values and the remainders of the pixel pairs, the secret bits are embedded. The experiment has been conducted to compute the performance of the proposed technique with regards to the image quality metrics like peak signal-to-noise ratio (PSNR), embedding capacity (EC), and FOBP. Results show that PSNR is optimal for vertical pairs with 39.17 dB whereas the EC is optimal for the diagonal pairs with 3.10 bits per pixel (BPP). Further, the proposed technique has shown exceptional attack resistance ability to regular & singular (RS) attack, salt & pepper (S&P) noise, pixel difference histogram (PDH) analysis, and subtractive pixel adjacency matrix (SPAM) steganalysis.

自从像素值差分（PVD）图像隐写术问世以来，它引起了该领域研究人员的极大兴趣。但是，大多数基于PVD的技术都面临掉落边界问题（FOBP）或错误提取问题（IEP）的问题。因此，为了解决这两个问题，本文提出了一种基于多方向像素值差分和模函数的技术。在嵌入过程中，原始图像（OI）分为2×2大小的像素块。然后，通过利用每个块的水平，垂直和对角线方向执行数据嵌入。对于2×2像素块，可以在三个方向中的任何一个上获得两个差值。接下来，使用差值和像素对的其余部分，嵌入秘密位。已经进行了实验，以针对像峰值信噪比（PSNR），嵌入容量（EC）和FOBP之类的图像质量度量来计算所提出技术的性能。结果表明，PSNR最佳垂直对为39.17 dB，而EC最佳对角对为3.10每像素像素（BPP）。此外，所提出的技术已显示出对常规和奇异（RS）攻击，盐和胡椒（S＆P）噪声，像素差异直方图（PDH）分析以及减法像素邻接矩阵（SPAM）隐写分析的出色抵抗能力。结果表明，PSNR最佳垂直对为39.17 dB，而EC最佳对角对为3.10每像素像素（BPP）。此外，所提出的技术已显示出对常规和奇异（RS）攻击，盐和胡椒（S＆P）噪声，像素差异直方图（PDH）分析以及减法像素邻接矩阵（SPAM）隐写分析的出色抵抗能力。结果表明，PSNR最佳垂直对为39.17 dB，而EC最佳对角对为3.10每像素像素（BPP）。此外，所提出的技术已显示出对常规和奇异（RS）攻击，盐和胡椒（S＆P）噪声，像素差异直方图（PDH）分析以及减法像素邻接矩阵（SPAM）隐写分析的出色抵抗能力。