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Deep learning decryption approach for asymmetric computer-generated holography (CGH) cryptosystem.

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    A new deep learning (DL) strategy enhances optical image decryption for asymmetric CGH cryptosystems. The ACGHC-Net achieves high-fidelity decryption with excellent robustness against noise and cropping, paving the way for keyless image encryption.

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    Area of Science:

    • Optics and Photonics
    • Computer Science
    • Cryptography

    Background:

    • Keyless management is a significant advantage in optical image decryption.
    • Asymmetric cryptosystems based on digital hologram (DRPE) and computer-generated holography (CGH) are gaining traction.
    • Phase truncation and chaotic phase masks offer unique properties for secure image encryption.

    Purpose of the Study:

    • To propose a high-fidelity deep learning (DL) decryption strategy for asymmetric DRPE-based CGH cryptosystems.
    • To develop a DL model capable of accurate and efficient decryption of ciphertext images.
    • To evaluate the robustness of the proposed decryption method against noise and image cropping.

    Main Methods:

    • A dataset of ciphertext and plaintext image pairs was generated.
    • A deep neural network, ACGHC-Net, was designed and trained using supervised learning.
    • The network was combined with phase truncation and chaotic iris phase masks for decryption.

    Main Results:

    • The ACGHC-Net achieved high decryption fidelity with an average cross-correlation coefficient (CC) of 0.998.
    • Excellent image quality was demonstrated with an average structural similarity (SSIM) of 0.895 and peak signal-to-noise ratio (PSNR) of 31.090 dB.
    • The network exhibited strong anti-noise and anti-cropping robustness for encrypted complex grayscale images.

    Conclusions:

    • The proposed ACGHC-Net provides an effective and robust solution for keyless decryption in asymmetric DRPE-based CGH cryptosystems.
    • The DL-based approach offers significant improvements in decryption speed and accuracy.
    • This method is expected to advance keyless decryption techniques in optical image encryption systems.