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An enhanced Huffman-PSO based image optimization algorithm for image steganography
Genetic Programming and Evolvable Machines ( IF 1.7 ) Pub Date : 2021-01-01 , DOI: 10.1007/s10710-020-09396-z
Neha Sharma , Usha Batra

It is crucial in the field of image steganography to find an algorithm for hiding information by using various combinations of compression techniques. The primary factors in this research are maximizing the capacity and improving the quality of the image. The image quality cannot be compromised up to a certain level as it breaks the concept of steganography by getting distorted visibly. The second primary factor is maximizing the data-carrying/embedding capacity, which makes the use of this technique more efficient. In this paper, we are proposing an image steganography tool by using Huffman Encoding and Particle Swarm Optimization, which will improve the performance of the information hiding scheme and improve overall efficiency. The combinational technique of Huffman PSO not only offers higher information embedment capabilities but also maintains the image quality. The experimental analysis and results on cover images along with different sizes of secret messages validate that the proposed HPSO scheme has superior results using parameters Peak-Signal-to-Noise-Ratio, Mean Square Error, Bit Error Rate, and Structural Similarity Index. It is also robust against statistical attacks.

中文翻译:

一种基于 Huffman-PSO 的增强型图像隐写优化算法

在图像隐写术领域,找到一种通过使用各种压缩技术组合来隐藏信息的算法至关重要。本研究的主要因素是最大化容量和提高图像质量。图像质量不会受到一定程度的影响,因为它通过明显扭曲打破了隐写术的概念。第二个主要因素是最大化数据承载/嵌入容量,这使得该技术的使用更加高效。在本文中,我们提出了一种使用霍夫曼编码和粒子群优化的图像隐写工具,这将提高信息隐藏方案的性能并提高整体效率。Huffman PSO 的组合技术不仅提供了更高的信息嵌入能力,而且还保持了图像质量。对覆盖图像以及不同大小的秘密消息的实验分析和结果验证了所提出的 HPSO 方案使用参数峰值信噪比、均方误差、误码率和结构相似性指数具有优越的结果。它还可以抵御统计攻击。
更新日期:2021-01-01
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