Laser & Optoelectronics Progress, Volume. 58, Issue 16, 1609001(2021)

Adaptive Image Block Hiding Technology Based on Optical Spatial-Frequency Domain Transform

Yan Wang1,2、* and Hongwei Niu1
Author Affiliations
  • 1Shanghai JoyReal Information Technology Co., Ltd., Shanghai 201112, China
  • 2OTTO Intelligent Technology (Haian) Co., Ltd., Haian, Jiangsu 226600, China
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    Aiming at the problem of large-capacity information embedded in information hiding technology reducing the concealment and robustness, an adaptive image block hiding technology based on optical spatial-frequency domain transform was proposed. The gray-level correlation analysis and echo state network were used to form the adaptive embedding mechanism. When the embedding capacity reached the saturation threshold, the embedding position was automatically adjusted using the mechanism based on the gray-level correlation order to avoid excessive deterioration in robustness. Based on this, the two-dimensional discrete cosine transform was used to hide images in the spatial-frequency domain and combined with the human eye’s characteristic of insensitivity to the optical high-frequency area to realize information hiding in the transform domain, thereby ensuring that the concealment was not affected. Simulation and comparative experiments prove that the visual perspective is unaffected after large-capacity information is embedded in the carrier image. After introducing Gaussian and salt and pepper noise interference and rotating and zooming geometric attacks, results show that the information carrier is insensitive to noise interference and geometric attacks, indicating the technology ensures large-capacity embedding while considering concealment and robustness.

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    Yan Wang, Hongwei Niu. Adaptive Image Block Hiding Technology Based on Optical Spatial-Frequency Domain Transform[J]. Laser & Optoelectronics Progress, 2021, 58(16): 1609001

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    Paper Information

    Category: Holography

    Received: Nov. 11, 2020

    Accepted: Dec. 8, 2020

    Published Online: Jul. 22, 2021

    The Author Email: Wang Yan (wolf_wong0444@sina.com)

    DOI:10.3788/LOP202158.1609001

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