Compression of 3D Optical Encryption Using Singular Value Decomposition
In this paper, we propose a compressionmethod for optical encryption using singular value decomposition (SVD). Double random phase encryption (DRPE), which employs two distinct random phase masks, is adopted as the optical encryption technique. Since the encrypted data in DRPE have the same size as...
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MDPI AG
2025-08-01
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| author | Kyungtae Park Min-Chul Lee Myungjin Cho |
| author_facet | Kyungtae Park Min-Chul Lee Myungjin Cho |
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| description | In this paper, we propose a compressionmethod for optical encryption using singular value decomposition (SVD). Double random phase encryption (DRPE), which employs two distinct random phase masks, is adopted as the optical encryption technique. Since the encrypted data in DRPE have the same size as the input data and consists of complex values, a compression technique is required to improve data efficiency. To address this issue, we introduce SVD as a compression method. SVD decomposes any matrix into simpler components, such as a unitary matrix, a rectangular diagonal matrix, and a complex unitary matrix. By leveraging this property, the encrypted data generated by DRPE can be effectively compressed. However, this compression may lead to some loss of information in the decrypted data. To mitigate this loss, we employ volumetric computational reconstruction based on integral imaging. As a result, the proposed method enhances the visual quality, compression ratio, and security of DRPE simultaneously. To validate the effectiveness of the proposed method, we conduct both computer simulations and optical experiments. The performance is evaluated quantitatively using peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and peak sidelobe ratio (PSR) as evaluation metrics. |
| format | Article |
| id | doaj-art-069f3a276401448ca45620ad8a74a8e2 |
| institution | DOAJ |
| issn | 1424-8220 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | MDPI AG |
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| spelling | doaj-art-069f3a276401448ca45620ad8a74a8e22025-08-20T03:02:51ZengMDPI AGSensors1424-82202025-08-012515474210.3390/s25154742Compression of 3D Optical Encryption Using Singular Value DecompositionKyungtae Park0Min-Chul Lee1Myungjin Cho2School of ICT, Robotics, and Mechanical Engineering, IITC, Hankyong National University, 327 Chungang-ro, Anseong 17579, Republic of KoreaGraduate School of Computer Science and Systems Engineering, Kyushu Institute of Technology, 680-4 Kawazu, Iizuka-shi 820-8502, Fukuoka, JapanSchool of ICT, Robotics, and Mechanical Engineering, IITC, Hankyong National University, 327 Chungang-ro, Anseong 17579, Republic of KoreaIn this paper, we propose a compressionmethod for optical encryption using singular value decomposition (SVD). Double random phase encryption (DRPE), which employs two distinct random phase masks, is adopted as the optical encryption technique. Since the encrypted data in DRPE have the same size as the input data and consists of complex values, a compression technique is required to improve data efficiency. To address this issue, we introduce SVD as a compression method. SVD decomposes any matrix into simpler components, such as a unitary matrix, a rectangular diagonal matrix, and a complex unitary matrix. By leveraging this property, the encrypted data generated by DRPE can be effectively compressed. However, this compression may lead to some loss of information in the decrypted data. To mitigate this loss, we employ volumetric computational reconstruction based on integral imaging. As a result, the proposed method enhances the visual quality, compression ratio, and security of DRPE simultaneously. To validate the effectiveness of the proposed method, we conduct both computer simulations and optical experiments. The performance is evaluated quantitatively using peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and peak sidelobe ratio (PSR) as evaluation metrics.https://www.mdpi.com/1424-8220/25/15/4742compressiondouble random phase encryptionsingular value decompositionvolumetric computational reconstruction |
| spellingShingle | Kyungtae Park Min-Chul Lee Myungjin Cho Compression of 3D Optical Encryption Using Singular Value Decomposition Sensors compression double random phase encryption singular value decomposition volumetric computational reconstruction |
| title | Compression of 3D Optical Encryption Using Singular Value Decomposition |
| title_full | Compression of 3D Optical Encryption Using Singular Value Decomposition |
| title_fullStr | Compression of 3D Optical Encryption Using Singular Value Decomposition |
| title_full_unstemmed | Compression of 3D Optical Encryption Using Singular Value Decomposition |
| title_short | Compression of 3D Optical Encryption Using Singular Value Decomposition |
| title_sort | compression of 3d optical encryption using singular value decomposition |
| topic | compression double random phase encryption singular value decomposition volumetric computational reconstruction |
| url | https://www.mdpi.com/1424-8220/25/15/4742 |
| work_keys_str_mv | AT kyungtaepark compressionof3dopticalencryptionusingsingularvaluedecomposition AT minchullee compressionof3dopticalencryptionusingsingularvaluedecomposition AT myungjincho compressionof3dopticalencryptionusingsingularvaluedecomposition |