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Technology of Information Security
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App. Res. of Comp. Printed Article
Vol. 42, 2025 No. 4
1217-1222

High-capacity reversible data hiding based on neighboring mean difference histogram

Xiong Tao1
Ding Haiyang1,2
Li Yajing1
1. College of Information Engineering, Beijing Institute of Graphic Communication, Beijing 102600, China
2. Information Security Center, Beijing University of Posts & Telecommunications, Beijing 100876, China
DOI: 10.19734/j.issn.1001-3695.2024.05.0265

Abstract

To address the issue of limited capacity in reversible data hiding(RDH), this paper proposed a neighboring mean difference reversible data hiding(NMDRDH) algorithm. The neighboring mean difference(NMD) calculated the difference between the average of two adjacent values and one of the values, minimizing the difference and making the data more concentrated. Firstly, it divided the image into blocks, then applied NMD on the blocks to generate a difference histogram. Finally, it embedded the secret information by shifting the difference histogram and utilizing the peak points. Because NMD generated a difference histogram with more peak points, this method could embed more secret information. Experimental results show that this algorithm achieves 100% accuracy in both original image recovery and secret information extraction. Compared to the classical difference histogram shifting method, this algorithm increases the embedding capacity by 43.7%. Moreover, while ensuring high capacity, the PSNR reaches above 42 dB, ensuring minimal distortion of the embedded image.

Foundation Support

国家自然科学基金项目(62472040)
北京市教委科研项目(KM202110015004)
北京市高等教育学会项目(MS2023204)
北京市数字教育研究课题(BDEC2023619095)
北京印刷学院博士启动金项目(27170120003/020,27170122006)
北京印刷学院科研基础研究一般项目(Ec202201)
北京印刷学院青年卓越项目(Ea202411)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2024.05.0265
Publish at: Application Research of Computers Printed Article, Vol. 42, 2025 No. 4
Section: Technology of Information Security
Pages: 1217-1222
Serial Number: 1001-3695(2025)04-034-1217-06

Publish History

[2025-04-05] Printed Article

Cite This Article

熊涛, 丁海洋, 李雅静. 基于相邻均值差直方图的高容量可逆信息隐藏算法 [J]. 计算机应用研究, 2025, 42 (4): 1217-1222. (Xiong Tao, Ding Haiyang, Li Yajing. High-capacity reversible data hiding based on neighboring mean difference histogram [J]. Application Research of Computers, 2025, 42 (4): 1217-1222. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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