Name
Abstract | ||
|---|---|---|
This paper presents a novel image compression-encryption scheme, which has the compression-confusion-diffusion Structure. Firstly, based on Chebyshev chaotic map, a Gauss measurement matrix is constructed and optimized, which is applied to compressive sensing. Then, an image compression-encryption algorithm is proposed by using a six-dimensional discrete chaotic map. In the proposed scheme, the original image is transformed into a sparse coefficient matrix by discrete wavelet transform, and the sparse coefficients are measured by using the optimized Gauss measurement matrix to get the measured values. Then, the measured values are quantized into integer values and the compressed image is obtained. Furtherly, the compressed image is encrypted by using a six-dimensional chaotic map. In the process of encryption, the plaintext image is divided into two parts, when encrypting the second part, the first part is used as part of the key. While encrypting the first part, the ciphertext of the second part is used as part of the key. Thus, the algorithm has strong confusion and diffusion effect and makes ciphertext sensitive to plaintext. Experimental results such as effects of compression-encryption, key space analysis, key sensitivity analysis, differential analysis, histograms analysis, information entropy analysis, and correlation coefficients analysis show that the proposed scheme is secure and has high application potential. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1007/s11042-020-09699-4 | MULTIMEDIA TOOLS AND APPLICATIONS |
Keywords | DocType | Volume |
Chaos,Image encryption,Compressive sensing,Discrete hyper-chaotic map | Journal | 79.0 |
Issue | ISSN | Citations |
43-44 | 1380-7501 | 3 |
PageRank | References | Authors |
0.39 | 0 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Shuqin Zhu | 1 | 14 | 2.98 |
| Congxu Zhu | 2 | 70 | 11.84 |
| Fu Yu | 3 | 23 | 3.09 |
| Weimeng Zhang | 4 | 3 | 0.39 |
| Xiaoting Wu | 5 | 3 | 0.39 |