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Improved Reference Image Encryption Methods Based on 2K Correction in the Integer Wavelet Domain Cover

Improved Reference Image Encryption Methods Based on 2K Correction in the Integer Wavelet Domain

Open Access
|Dec 2019

Abstract

Many visually meaningful image encryption (VMIE) methods have been proposed in the literature using reference encryption. However, the most important problems of these methods are low visual quality and blindness. Owing to the low visual quality, the pre-encrypted image can be analyzed simply from the reference image and, in order to decrypt nonblind methods, users should use original reference images. In this paper, two novel reference image encryption methods based on the integer DWT (discrete wavelet transform) using 2k correction are proposed. These methods are blind and have high visual quality, as well as short execution times. The main aim of the proposed methods is to solve the problem of the three VMIE methods existing in the literature. The proposed methods mainly consist of the integer DWT, pre-encrypted image embedding by kLSBs (k least significant bits) and 2k correction. In the decryption phase, the integer DWT and pre-encrypted image extraction with the mod operator are used. Peak signal-to-noise ratio (PSNR) measures the performances of the proposed methods. Experimental results clearly illustrate that the proposed methods improve the visual quality of the reference image encryption methods. Overall, 2k correction and kLSBs provide high visual quality and blindness.

DOI: https://doi.org/10.2478/amcs-2019-0060 | Journal eISSN: 2083-8492 | Journal ISSN: 1641-876X
Language: English
Page range: 817 - 829
Submitted on: Mar 19, 2019
Accepted on: Jul 10, 2019
Published on: Dec 31, 2019
Published by: University of Zielona Góra
In partnership with: Paradigm Publishing Services
Publication frequency: 4 issues per year

© 2019 Turker Tuncer, Sengul Dogan, Ryszard Tadeusiewicz, Paweł Pławiak, published by University of Zielona Góra
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.