Evaluation of bioinspired algorithms for image optimization

作     者：Sharma, Neha Chakraborty, Chinmay 

作者机构：Chandigarh Univ Mohali India Birla Inst Technol Jharkhand India 

出 版 物：《JOURNAL OF ELECTRONIC IMAGING》 (电子成像杂志)

年 卷 期：2022年第31卷第4期

页      面：041206-041206页

核心收录：

学科分类：0808[工学-电气工程] 1002[医学-临床医学] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 0702[理学-物理学] 

主　　题：peak signal-to-noise ratio mean square error particle swarm optimization ant colony optimization firefly algorithm artificial bee colony image optimization image steganography bit error rate bioinspired algorithms computationally intelligent algorithms 

摘      要：Steganography is a technique for concealing sensitive information behind a specific media source, such as an image, audio, or video file, in such a way that the concealed data are invisible to everyone. Many algorithms have been developed to optimize this process for better output. We aim to identify the different optimization algorithms used in image steganography after embedding the data to improve the resilience, visibility, and payload carrying capacity. Additionally, we highlight several bioinspired algorithms, including particle swarm optimization, ant colony optimization, firefly optimization, and artificial bee colony optimization, and evaluate through performance measures such as peak signal-to-noise ratio (PSNR) and mean square error (MSE). The performance metrics generated from the collected data indicate that the firefly method produced a higher PSNR and a lower MSE, namely 72.42 dB and 0.13, respectively. The methods are evaluated in terms of their ability for data embedding, robustness, and imperceptibility.