Digital Image Hiding Technology Based on Arnold Transformation and Image Blending

TIAN Peng-hui; SUI Li-chun

Chinese

您当前的位置：

首页 >

文章列表页 >

Digital Image Hiding Technology Based on Arnold Transformation and Image Blending

更新时间：2026-09-04

- Digital Image Hiding Technology Based on Arnold Transformation and Image Blending
- Vol. 30, Issue 4, Pages: 10-13(2013)
- 作者机构：
  
  1. 1 长安大学地质工程与测绘学院,陕西,西安,710054
  2. 2 西安工业大学机构计算机科学与工程学院,陕西,西安,710032
- 作者简介：
- 基金信息：
- DOI：
  CLC：
- Published：2013
- 稿件说明：
移动端阅览
田鹏辉, 隋立春. 基于Arnold变换和图像融合的数字图像隐藏算法[J]. 微电子学与计算机, 2013, 30(4): 10-13.

TIAN Peng-hui, SUI Li-chun. Digital Image Hiding Technology Based on Arnold Transformation and Image Blending[J]. 2013, 30(4): 10-13.
田鹏辉, 隋立春. 基于Arnold变换和图像融合的数字图像隐藏算法[J]. 微电子学与计算机, 2013, 30(4): 10-13. DOI：

TIAN Peng-hui, SUI Li-chun. Digital Image Hiding Technology Based on Arnold Transformation and Image Blending[J]. 2013, 30(4): 10-13. DOI：

摘要

针对传统Arnold反变换需要先计算出变换周期和恢复图像时间较长的弱点

提出了快速Arnold反变换方法

该方法利用6个方程组求解得到.实验证明该方法可行、效果好

大大节省了恢复原始图像的时间

提高了传统Arnold算法的效率

同时具有良好的鲁棒性.

Abstract

Traditional Arnold inverse transformation needs to calculate the cycle of transformation

and it spends on more times in images recovery.In this paper a recovery method of hidden digital image based on fast Arnold inverse transformation is proposed.It needs to solve six equations set.Experimental results show the proposed method has high robustness

improves the efficiency of image restoration than the traditional Arnold inverse transformation.

关键词

Keywords

references

Views

下载量

CSCD

Alert me when the article has been cited

提交

Tools

Publicity Resources

Design of ultra-low power real-time clock circuits

Steganography model guided by attention mechanism and improved dense convolution

A review of large model development: technological evolution from BERT to Deepseek

Monte carlo analysis of V-layout trench SiC neutron detector

Implementation and verification of a dual-chain power gating strategy for low power design

Related Author

No data

Related Institution

No data

AI问答

Postal code：100079
Tel：（010）53879206 Email：tmw@bjxintong.com.cn
Technical support is provided by Beijing Founder electronics co., LTD 京ICP备09082226号-64 京公网安备11010602201714号
It is recommended to read the content of this site in Chrome&IE9+. Please switch to extreme mode in browser 360.
Cookies We use cookies to help provide and enhance our service and tailor content. By continuing, you agree to the use of cookies.

⁰