LSB matching revisited is an LSB-based approach for image steganography. This method is a type of coding to increase the capacity of steganography. In this method, two bits of the secret message are hidden in two pixels with only one change. But this method provides no idea for hiding a message with a large number of bits. In other words, this method works only for , where is the number of bits in a block of the secret message. In this paper, we propose an improved version of the LSB matching revisited approach, which works for . The proposed scheme contains two phases including embedding and extracting the message. In the embedding phase, we first convert the secret message into a bit-stream, and then the bit-stream is divided into a set of blocks including bits in each block. Then we choose pixels for hiding such bits of the secret message. In the next step, we choose the operations needed to generate such a message. Finally, we perform the obtained operations over the coefficients to hide the secret message. The proposed approach needs fewer changes than LSB MR when . The capacity of the proposed approach is higher than the F5 method where this value for is bigger than 75%. For example, the capacity of our scheme is 75% higher than the capacity of F5 for . The proposed method can be used in the first step of every steganography method to reduce the change in the stego image. Therefore, this method is a new coding method for steganography. Our experimental results using steganalysis show that using our method provides around 10% higher detection error for SRNet over two steganography schemes.

中文翻译：

---

再谈基于LSB匹配的隐写术编码新方法

重新讨论的LSB匹配是一种基于LSB的图像隐写方法。这种方法是一种增加隐写能力的编码方式。在这种方法中，秘密消息的两位隐藏在两个像素中，只有一个变化。但是这种方法对于隐藏具有大量比特的消息没有任何想法。换句话说，此方法仅适用于，其中是秘密消息块中的位数。在本文中，我们提出了LSB匹配重访方法的改进版本，该方法适用于。所提出的方案包含两个阶段，包括嵌入和提取消息。在嵌入阶段，我们首先将秘密消息转换为比特流，然后将比特流划分为一组块，每个块中均包含比特。然后，我们选择像素以隐藏秘密消息的此类位。在下一步中，我们选择生成此类消息所需的操作。最后，我们对系数执行获得的运算以隐藏秘密消息。与LSB MR相比，建议的方法需要的更改更少。拟议方法的能力是 高于F5方法，其中 大于75％。例如，我们方案的容量比F5的容量高75％。所提出的方法可用于每种隐写术方法的第一步，以减少隐身图像的变化。因此，该方法是一种新的隐写术编码方法。我们使用隐写分析得出的实验结果表明，与两种隐写术方案相比，使用本方法可为SRNet提供约10％的更高检测误差。