针对LSB匹配隐写的评价策略与改进方法

Evaluation and Improvement for LSB Matching Steganography

以Mielikainen提出的LSB匹配算法为基础,通过分析秘密信息对与载体像素对之间的不同匹配顺序对隐写算法性能的影响,提出了一个三级得分评价策略.根据此评价策略的指导,采用粒子群优化算法寻找出最优的信息对嵌入顺序,并在此基础上对Mielikainen的方法进行改进,提出了一种新的隐写算法.实验结果表明,在嵌入相同大小秘密信息的条件下,提出的算法减少了载体图像中灰度值发生变化的像素点数,从而有效提高了隐秘图像的视觉感知质量.

By analyzing the performance impact of different matching orders between secret messages and cartier pixels on the algorithm, this paper proposes a three-level score evaluating strategy based on the pair-wise LSB matching method proposed by Mielikainen. Using the new evaluating strategy, a particle swarm optimization algorithm is applied to search for an optimal solution among all such permutation orders, based on which a novel steganographic algorithm is presented aiming at improving Mielikaine＇s method. The experimental results indicate that, with the same amount of secret information, the proposed method further reduces the number ofpixels with changed gray-values in the carrier image after embedding the secret messages. Therefore, the stegano image achieves higher visual perceptual quality using the proposed method than Mielikainen＇s method.