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A visual security image encryption algorithm based on 1D-CHCCM and super-resolution reconstruction
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DOI：10.1016/j.dsp.2026.105981.png)
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Abstract
En 中文
In visual security image encryption algorithms, simultaneously ensuring security and high-quality restored images remains challenging. In this paper, we propose a method that incorporates deep learning-based super-resolution reconstruction as a key post-processing step after the encryption-decryption steps. This approach aims to achieve high-quality reconstructed images while maintaining decryption security. Specifically, a 1D Chebyshev-hyperbolic composite chaotic map (1D-CHCCM) is firstly proposed. Its superior chaotic behavior and stability are validated through multidimensional analysis, including Lyapunov exponent, sample entropy, and permutation entropy. To address the traditional channel independent processing, the symmetric cross-channel circular scrambling (SC3S) and odd-even alternating diffusion (OEAD) are proposed. These mechanisms treat color images as unified entities to enhance resistance to attacks. Furthermore, for visual concealment during transmission, a texture-based adaptive data hiding (ATADH) scheme is utilized to guarantee steganographic images (STIs) are visually indistinguishable. After decryption, the decrypted image is fed into a Transformer-based super-resolution reconstruction network to obtain the final high-quality image. Quantitative analysis reveals that the proposed algorithm achieves a correlation coefficient below 0.003, an information entropy of 7.9973, and NPCR/UACI scores of 99.61% and 33.42%. In terms of visual quality, the STIs maintain excellent imperceptibility with a PSNR of 48.8 dB, and these reconstructed images have reached a PSNR of 41 dB. These results confirm that the goal of balancing security and high-quality image restoration is achieved.
Keywords:
1D-CHCCM
super-resolution reconstruction
image encryption
chaotic map
steganography
Journal
D
IF:
3
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653
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