JAMC
Image Encryption Based on Compressed Sensing, Chaotic System and Slant Haar Type Orthogonal Transforms
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Abstract
In the era of big data, how to encrypt images and ensure image security is an important research hotspot. In this paper, an efficient image encryption scheme is proposed based on the Slant Haar type orthogonal transform (SHTOT), compressed sensing (CS), and a chaotic system. First, the original image is transformed by our provided SHTOT, which contains specific parameters that may be regarded as an encryption key. Then, the transformed coefficients are compressed and measured simultaneously by using CS, during which some pseudo-random sequences produced by the chaotic system coupling sine mapping and logistic mapping are employed to generate the measurement matrix for CS. Next, the Arnold transform is utilized for the scrambling of the CS measured values. Based on this, some other pseudo-random sequences are used for the modification of the quantized CS measured values. Finally, the decryption operation is performed according to the reverse process described above, and a blind Sparsity Adaptive Matching Pursuit algorithm in CS is applied to the image reconstruction. Simulation and experimental analysis demonstrate that the image encryption scheme provided in this paper has good performance in image compression and encryption from the perspective of visual effect, information entropy, correlation coefficient, key sensitivity, key space, and robustness.
Keywords
Image encryption; chaotic system; compressed sensing; Arnold transform; Slant Haar type orthogonal transform
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How to cite this paper
Image Encryption Based on Compressed Sensing, Chaotic System and Slant Haar Type Orthogonal Transforms
How to cite this paper: Xiuqiao Xiang, Qixin Cai, Baochang Shi, Jianga Shang. (2026) Image Encryption Based on Compressed Sensing, Chaotic System and Slant Haar Type Orthogonal Transforms. Journal of Applied Mathematics and Computation, 10(2), 59-75.
DOI: http://dx.doi.org/10.26855/jamc.2026.06.001
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