Journal of Computer Applications ›› 2019, Vol. 39 ›› Issue (2): 483-487.DOI: 10.11772/j.issn.1001-9081.2018071471

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3D medical image reversible watermarking algorithm based on unidirectional prediction error expansion

LI Qi, YAN Bin, CHEN Na, YANG Hongmei   

  1. College of Electronics, Communication and Physics, Shandong University of Science and Technology, Qingdao Shandong 266590, China
  • Received:2018-07-16 Revised:2018-09-08 Online:2019-02-10 Published:2019-02-15
  • Supported by:
    This work is partially supported by the National Natural Science Foundation of China (61272432), the Shandong Provincial Natural Science Foundation (ZR2014JL044).


李琦, 颜斌, 陈娜, 杨红梅   

  1. 山东科技大学 电子通信与物理学院, 山东 青岛 266590
  • 通讯作者: 颜斌
  • 作者简介:李琦(1996-),男,山东菏泽人,硕士研究生,主要研究方向:加密域的可逆信息隐藏;颜斌(1973-),男,山东荣成人,副教授,博士,主要研究方向:多媒体信息安全;陈娜(1988-),女,山东滕州人,讲师,博士,主要研究方向:密码学、多媒体信息安全;杨红梅(1969-),女,山西太原人,副教授,博士,主要研究方向:多媒体信息安全。
  • 基金资助:

Abstract: For the application of reversible watermarking technology in three-Dimensional (3D) medical images, a 3D medical image reversible watermarking algorithm based on unidirectional prediction error expansion was proposed. Firstly, the intermediate pixels were predicted according to the 3D gradient changes between them and their neighborhood pixels to obtain the prediction errors. Then, considering the features of the 3D medical image generated by magnetic resonance imaging, the external information was embedded into the 3D medical image by combining unidirectional histogram shifting with prediction error expansion. Finally, the pixels were re-predicted to extract the external information and restore the original 3D image. Experimental results on MR-head and MR-chest data show that compared with two-dimensional (2D) gradient-based prediction, the mean absolute deviation of prediction error produced by 3D gradient-based prediction are reduced by 1.09 and 1.40, respectively; and the maximal embedding capacity of each pixel is increased by 0.0456 and 0.1291 bits, respectively. The proposed algorithm can predict the pixels more accurately and embed more external information, so it is applicable to 3D medical image tempering detection and privacy protection for patients.

Key words: reversible watermarking, three-Dimensional (3D) medical image, gradient, prediction error expansion, histogram shifting

摘要: 对于可逆水印技术在三维医学图像中的应用问题,提出一种基于单向预测误差扩展的三维医学图像可逆水印算法。首先根据像素间的三维梯度变化预测像素从而得到预测误差;然后结合磁共振成像生成的三维医学图像的特征,采用单向直方图位移与预测误差扩展相结合的方法将外部信息嵌入至三维医学图像;最后,重新预测像素,提取外部信息,恢复原始三维图像。实验结果表明,在MR-head和MR-chest测试数据体上,与二维梯度预测相比,所提算法预测误差的平均绝对偏差分别降低1.09和1.40,每个像素的最大嵌入容量分别增加0.0456比特和0.1291比特,从而能够更准确地预测像素值,嵌入更多的外部信息。该算法可应用于对三维医学图像的篡改检测以及患者隐私保护。

关键词: 可逆水印, 三维医学图像, 梯度, 预测误差扩展, 直方图位移

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