Determining the Capacity Parameters in PEE-Based Reversible Image Watermarking

2012 ◽  
Vol 19 (5) ◽  
pp. 287-290 ◽  
Author(s):  
Jiantao Zhou ◽  
Oscar C. Au
2019 ◽  
Vol 8 (2S11) ◽  
pp. 3567-3570

Health Informatics systems preserves the patient’s digital records. Two techniques that help in this process are watermarking and encryption. In this paper a reversible image watermarking scheme with logistic encryption is presented. The reversible watermarking is utilizing the concept of integer wavelet transform. The image is divided into sub bands and then the binary data is hidden in these sub bands. The watermarked wavelet sub bands are passed through logistic encryption module which scrambles the coefficients. These coefficients are then sent to inverse wavelet transform for image reconstruction. This process helps encrypt the image though spectral scrambling, thus resulting in faster and better encryption. The proposed algorithm outperforms the exiting algorithms in terms of execution time and the level of encryption.


2019 ◽  
Vol 12 (15) ◽  
pp. 1-8
Author(s):  
T. Sujatha ◽  
Susan Augustine ◽  
J. Granty Regina Elwin ◽  
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2017 ◽  
Vol 7 (1.3) ◽  
pp. 42
Author(s):  
Bennilo Fernandes.J ◽  
Sivakannan S ◽  
Prabakaran N ◽  
G. Thirugnanam

In this contemporary world procuring our confidential data against some unknown person is very significant. Thus to have a high reliability of data security watermarking technique is applied before transmitting the data. This proposed work LCWT and DGT decomposition gives an effective technique to protect hypertensive related information based on reversible watermarking. LCWT has the superiority of multi-resolution fundamental analysis of wavelet transform and reflects representation of image domain in LCT. And using DGT decomposition the patient information has to embed inside high frequency subband wavelet and the watermarked information will be extracted by the receiver without any loss, to reconstruct the original image information. The reliability of the proposed method is analyzed by comparing the experimental results of similarity index, normalization and peak signal to noise ratio.


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