Fig. 1. Optical implementation of double random phase encoding. (a) Encryption; (b) decryption
Fig. 2. Information processing flowchart for different compression strategies in optical compression-encryption system. (a) Plaintext compression; (b) ciphertext compression; (c) synchronized compression
Fig. 3. An example of information compression by using the concentration of energy in the transform domain
Fig. 4. Principle of G-S algorithm
Fig. 5. Single pixel camera based on compressive sensing
[41] Fig. 6. Double-image encryption based on frequency spectral fusion
[44] Fig. 7. Simulation results of multiple-image encryption based on frequency spectral fusion
[44]. (a) Original images; (b) ciphertext; (c) decrypted images
Fig. 8. Multiple-image compression and encryption based on Radon transform
[52] Fig. 9. Image encryption and decryption process based on compression sensing and dual random phase coding system
[55] Fig. 10. Simulation results of image encryption system based on compression sensing and double random phase coding
[55]. (a) Original image; (b) image downsampled by sensing matrix; (c) host image; (d) ciphertext; (e) combined image containing cipher information; (f) reconstructed image
Fig. 11. Schematic of optical encryption process based on spatial multiplexing and compression sensing
[58] Fig. 12. Schematic of optical decryption process based on spatial multiplexing and compression sensing
[58] Fig. 13. Multiple-image encryption based on position multiplexing
[63]. (a) Encryption; (b) decryption
Fig. 14. Numerical simulation results of multiple-image encryption scheme based on position multiplexing
[63]. (a) Ciphertext; (b) decryption corresponding to position
; (c) result of Gaussian filtering on the image shown in Fig. 14 (b); (d) decryption corresponding to position
Fig. 15. Theta-modulation-based multiple-image encryption
[71] Fig. 16. Reconstruction of ciphertexts in theta-modulation-based multiple-image encryption
[71] Fig. 17. Reconstruction of plaintexts in theta-modulation-based multiple-image encryption
[71] Fig. 18. Multiple-image encryption based on angular multiplexing of CCD
[75] Fig. 19. Spectrum of the synthetic ciphertext
of
multiple-image encryption based on angular multiplexing of CCD
[75]. (a) Simulation result; (b) experimental result
Fig. 20. Decrypted results obtained by quantizing each pixel value in the ciphertext by different orders
[30]. (a) 4 bits; (b) 3 bits; (c) 2 bits
Fig. 21. Optical ciphertext compression method based on deep learning
[82]. (a) Compression; (b) decompression
Fig. 22. Comparison of the deep-learning-based optical ciphertext compression approach with JPEG and JPEG2000
[82] Fig. 23. Optical encryption based on compressive ghost imaging encryption
[29] Fig. 24. Decrypted results using compressive ghost imaging
[29]. (a) Plaintext; (b) decrypted result obtained by conventional method under 3500 samplings; (c) decrypted result obtained by compressive sensing under 3500 samplings; (d) decrypted result obtained by compressive sensing under 200 samplings
Fig. 25. Encryption system based on single pixel imaging, phase shifting holography, and random phase coding
[90] Fig. 26. Decryption result of gray image obtained by encryption system
[90]. (a) Plaintext; (b) one of the encrypted holograms on the DMD plane; (c) retrieved image of about 256×256×42.1% measurements, where 256×256 denotes the pixel count and 42.1% denotes the sampling ratio
Fig. 27. Optical decryption scheme of multi-image encryption system based on multi-plane phase recovery and interference principle
[93] Fig. 28. Iterative algorithm of multi-image encryption system based on multi-plane phase recovery algorithm and interference principle
[93] Fig. 29. Multiple-image encryption based on 3D space and phase retrieval algorithm
[94] Fig. 30. Multiple-image encryption based on azimuth multiplexing and phase retrieval algorithm
[95] Fig. 31. Iterative cryptosystem based on amplitude constraint in input plane
[97]. (a) Decryption optical path and iterative algorithm basis; (b) amplitude constraint in input plane; (c) amplitude constraint in output plane
Fig. 32. Ciphertext combination method based on spatial multiplexing
[97] Fig. 33. Optical encryption based on
correlator
[98] Fig. 34. Secret sharing (multiple-image encryption) system based on metasurface and iterative algorithm
[33] Fig. 35. Optical diffractive-imaging-based encryption scheme
Fig. 36. Effect of decryption algorithm of single exposure optical diffraction imaging encryption system
[107]. (a) Decrypted image; (b) dependence of CC on iteration number; (c) dependence of CC on iteration number corresponding to the first iterative procedure; (d) dependence of CC on iteration number corresponding to the second iterative procedure
Fig. 37. Multi-image encryption system based on multimode phase retrieval algorithm and focal length multiplexing
[110] Fig. 38. Relationship between the quality of the decrypted images (CC) and the iteration number in the multi-image encryption system based on multimode phase retrieval algorithm and focal length multiplexing
[110] Fig. 39. Single exposure color image encryption system based on multimodal diffraction imaging
[111] Fig. 40. Multiple-image encryption based on compressive holography
[114] Fig. 41. Decrypted results of multiple-image encryption based on compressive holography
[114]. (a)-(c) Plaintexts; (d) one of the holograms; (e)-(g) decrypted results
Compression strategy | Compression method |
---|
Plaintext compression | Transform domain compression | Compressive sensing | Ciphertext compression | Parameter multiplexing compression | Classical compression | Compressive sensing | Synchronized compression | Iterative phase retrieval algorithm | Compressive sensing |
|
Table 1. Compression strategies and methods for optical image compression-encryption
Hol.no. | Size(kB) | LZ77(kB) | LZW(kB) | Huff.(kB) | BW(kB) | Compression ratio |
---|
LZ77 | LZW | Huff. | BW |
---|
1 | 65,536 | 62,651 | 65,536 | 62,529 | 63,869 | 1.05 | 1.00 | 1.05 | 1.03 | 2 | 65,536 | 62,644 | 65,536 | 62,519 | 63,836 | 1.05 | 1.00 | 1.05 | 1.03 | 3 | 65,536 | 62,645 | 65,536 | 62,515 | 63,823 | 1.05 | 1.00 | 1.05 | 1.03 | 4 | 65,536 | 62,643 | 65,536 | 62,515 | 63,825 | 1.05 | 1.00 | 1.05 | 1.03 | 5 | 65,536 | 62,641 | 65,536 | 62,513 | 63,825 | 1.05 | 1.00 | 1.05 | 1.03 | Averages: | | | | | | 1.05 | 1.00 | 1.05 | 1.03 |
|
Table 2. Results by applying several classical compression methods to the original ciphertext
[30] Bits | Size(kB) | LZ77(kB) | LZW(kB) | Huff.(kB) | BW(kB) | Compression ratio |
---|
LZ77 | LZW | Huff. | BW |
---|
2 | 65,536(16,384) | 47 | 42 | 1027 | 32 | 1394(349) | 1560(390) | 64(16) | 2048(512) | 3 | 65,536(16,384) | 1138 | 1006 | 1317 | 1097 | 58(14) | 65(16) | 50(12) | 60(15) | 4 | 65,536(16,384) | 2120 | 1963 | 1991 | 2084 | 31(7.7) | 33(8.3) | 33(8.2) | 31(7.9) | 5 | 65,536(16,384) | 3097 | 2969 | 3021 | 2985 | 21(5.3) | 22(5.5) | 22(5.4) | 22(5.5) | 6 | 65,536(16,384) | 4003 | 4018 | 3923 | 3901 | 16(4.1) | 16(4.1) | 17(4.2) | 17(4.2) | 7 | 65,536(16,384) | 4732 | 5124 | 4784 | 4795 | 14(3.5) | 13(3.2) | 14(3.4) | 14(3.4) | 8 | 65,536(16,384) | 5460 | 6236 | 5613 | 5659 | 12(3.0) | 11(2.6) | 12(2.9) | 12(2.9) |
|
Table 3. Results by applying several classical compression methods to the quantized ciphertext
[30] Compression strategy | Compression method | Frame | Advantages and disadvantages |
---|
Plaintext compression | Transform domain compression | | This method always offers high quality decryption,but the independence between the compression/decompression and the encryption/decryption leads to time consumption. | Compressive sensing | This method always offers high quality decryption,but the decompression is time-consuming;meanwhile,the independence between the compression/decompression and the encryption/decryption leads to time consumption. | Ciphertext compression | Parameter multiplexing compression | | This method always suffers from low-quality decrypted results caused by cross-talk noise,but the decompression and decryption are always carried out simultaneously with a pure optical manner. Some preprocessing or postprocessing approaches can be adopted to alleviate the cross-talk noise at the cost of time. | Classical compression | The independence between the compression/decompression and the encryption/decryption leads to time consumption. The quality of the decryption will seriously degrade in the case of a high compression ratio;however,deep learning provides a new avenue for coping with such issues. | Compressive sensing | This method enables simultaneously compression and encryption,and it is widely used in cryptosystems based on ghost/single-pixel imaging. This method can always achieve a high compression ratio,but the decryption(decompression)is time-consuming. | Synchronized compression | Iterative phase retrieval algorithm | Iteratively encryption,optically decryption | The encryption procedure is time-consuming,but the decryption(decompression)can always be performed optically. The quality of the decrypted images is relatively high. | Optically encryption,iteratively decryption | The encryption procedure can always be performed optically,but the decryption(decompression)procedure is time-consuming. The quality of the decrypted images is relatively high. | Compressive sensing | | This method enables simultaneously compression and encryption with a pure optical manner,but the decryption(decompression)procedure is time-consuming. |
|
Table 4. Comparison and analysis of the aforementioned compression methods