Improved DE-Based Reversible Watermarking Using Sorting and Histogram Shifting

Author(s):  
Fei Peng ◽  
Yi Luo
2020 ◽  
Vol 16 (5) ◽  
pp. 155014772091701 ◽  
Author(s):  
Xin Tang ◽  
Linna Zhou ◽  
Dan Liu ◽  
Weijie Shan ◽  
Yi Zhang

Histogram shifting is an effective manner to achieve reversible watermarking, which works by shifting pixels between the peak point and its nearest zero point in histogram to make room for watermark embedding. However, once zero point is absent, the algorithm suffers from overflowing problem. Even though some works attempt to deal with this risk by introducing auxiliary information, such as a location map, they occupy a lot of embedding capacity inevitably. In this article, in order to deal with overflowing problem efficiently, we propose a border following–based reversible watermarking algorithm for images. With the help of border following algorithm and pre-processing, available regions with at least one zero point are recognized to embed watermark so that auxiliary information is not needed any more. And the algorithm utilized also ensures the same border can be re-recognized from the watermarked image without error, thus the correctness is also guaranteed. The performance of the proposed algorithm is evaluated using classic image datasets in this area, and the results not only validate the effectiveness of the proposed algorithm but also indicate its advantages compared with the classic histogram shifting–based reversible watermarking algorithm as well as the state of the art.


2013 ◽  
Vol 8 (1) ◽  
pp. 111-120 ◽  
Author(s):  
G. Coatrieux ◽  
Wei Pan ◽  
N. Cuppens-Boulahia ◽  
F. Cuppens ◽  
C. Roux

2016 ◽  
Vol 2016 ◽  
pp. 1-11 ◽  
Author(s):  
Laicheng Cao ◽  
Hao Zhou

In order to effectively increase embedding capacity and completely extract the watermarking information in information hiding of encrypted images, a new reversible watermarking embedding algorithm based on rhombus prediction model and difference histogram shifting ideas is proposed. Firstly, the images are pretreated according to rhombus prediction model. Then, the watermarking information is embedded in encrypted images by effective combination of homomorphism encryption scheme and reversible watermarking techniques. Finally, the watermarking information is completely extracted and the images are recovered based on computed difference histogram from left to right and from top to bottom. So, the efficiency and reversibility are ensured when watermarking information is embedded in encrypted image. Experiment results show that the proposed algorithm is simple and easy to realize, the embedding capacity is effectively increased, watermarking information is completely reversible, and the image can be recovered with no distortion.


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