Performance Analysis of Adaptive Variational Mode Decomposition Approach for Image Encryption
Feng Heng, Ruru Liu, Zuo Sun · 2020
A mapping function relation is generated by a variational mode decomposition (VMD) transform, and an adaptive image encryption algorithm based on VMD is proposed. The image sequence is generated using VMD is divided into high frequency, middle frequency, and low frequency according to the entropy value of its mode transformation. The advantages of this algorithm are that the cross-mapping is generated according to VMD, the low-frequency part is the main energy concentration area of the image, the image processing encryption is carried out in the other generated images, the encryption does not affect the original image, and the robustness is improved. The simulation results showed that the algorithm had a good effect of encryption and restoration by measuring the root mean square error and the Euclidean distance. Experiment showed that the proposed method was more robust to the complex distribution of faces than the existing methods considered, yielding favourably comparable results to the state-of-the-art methods on data encryption. The results also showed that the proposed method was scalable in other areas of datasets. Furthermore, we showed that the proposed method did not need the number of features as a prior, was aware of noises and outliers, and could be extended to a multi-view version for more accurate clustering accuracy. These steps, which should require generation of the final output from the styled paper, are mentioned here in this paragraph. First, users have to run "Reference Numbering" from the "Reference Elements" menu; this is the first step to start the bibliography marking (it should be clicked while keeping the cursor at the beginning of the reference list). After the marking is complete, the reference element runs all the options under the "Cross Linking" menu.