CN115065762B - 3D image encryption method based on computing ghost imaging - Google Patents
3D image encryption method based on computing ghost imaging Download PDFInfo
- Publication number
- CN115065762B CN115065762B CN202210662561.2A CN202210662561A CN115065762B CN 115065762 B CN115065762 B CN 115065762B CN 202210662561 A CN202210662561 A CN 202210662561A CN 115065762 B CN115065762 B CN 115065762B
- Authority
- CN
- China
- Prior art keywords
- eia
- image
- light
- key
- cellular automaton
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
Classifications
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
- H04N1/32—Circuits or arrangements for control or supervision between transmitter and receiver or between image input and image output device, e.g. between a still-image camera and its memory or between a still-image camera and a printer device
- H04N1/32101—Display, printing, storage or transmission of additional information, e.g. ID code, date and time or title
- H04N1/32144—Display, printing, storage or transmission of additional information, e.g. ID code, date and time or title embedded in the image data, i.e. enclosed or integrated in the image, e.g. watermark, super-imposed logo or stamp
- H04N1/32149—Methods relating to embedding, encoding, decoding, detection or retrieval operations
- H04N1/32267—Methods relating to embedding, encoding, decoding, detection or retrieval operations combined with processing of the image
- H04N1/32272—Encryption or ciphering
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
- G06F21/60—Protecting data
- G06F21/602—Providing cryptographic facilities or services
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T9/00—Image coding
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
- H04N1/44—Secrecy systems
- H04N1/448—Rendering the image unintelligible, e.g. scrambling
- H04N1/4486—Rendering the image unintelligible, e.g. scrambling using digital data encryption
Landscapes
- Engineering & Computer Science (AREA)
- Multimedia (AREA)
- Theoretical Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Signal Processing (AREA)
- Computer Hardware Design (AREA)
- Computer Security & Cryptography (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Bioethics (AREA)
- Length Measuring Devices By Optical Means (AREA)
Abstract
The application provides a 3D image encryption method based on computed ghost imaging, which utilizes an integrated imaging extraction technology to convert a 3D object into a micro-image array to obtain a plaintext. The resulting array of microimages is converted into a corresponding binary image and used as input to a cellular automaton to obtain a series of two-dimensional random masks, the rules and initial parameters of the cellular automaton being used as keys. And encrypting the plaintext by using a random mask generated by a ghost imaging calculation technology and a cellular automaton to obtain a series of light intensity values, namely ciphertext. In addition, in the step of calculating ghost images, fresnel diffraction occurs in the laser during the propagation process, so that the light field information is changed, and therefore, the propagation distance of the laser is also used as a key. The receiving end calculates the real light intensity distribution of the micro-image array surface during encryption by using the secret key, inputs the real light intensity distribution and the ciphertext into the association algorithm, so as to decrypt and obtain the micro-image array, and then reconstructs the original 3D object image by using the integrated imaging.
Description
Technical Field
The application relates to a ghost imaging calculation technology, an integrated imaging technology and a cellular automaton coding technology.
Background
In network communications, images are an important bearer of information. With the rise of 3D display technology, 3D image technology including 3D information has also been newly developed. The 3D image information is transmitted by a network, meanwhile, the safety problem is brought, and the problem that the 3D image is stolen by lawbreakers and huge loss is brought to related enterprises is avoided in order to reduce the potential safety hazard of the 3D image in the transmission process, so that the encryption research on the 3D image is urgent.
Image encryption is an important means for protecting images, and cellular automaton coding technology is one of the important methods. The cellular automaton coding technology is an automatic coding technology, and can generate pseudo-random sequences according to different rules and parameters, so that the encryption of images is realized. However, the 3D image has a special structure, and contains a larger amount of data than the conventional 2D image, and if the 3D image is directly encrypted by using the conventional image encryption method, the encryption process is very complicated and consumes a relatively high amount of power. The integrated imaging is an automatic three-dimensional and multi-view field 3D display technology, has a simple structure, is free from three-dimensional viewing visual fatigue, and is a hot spot for researching the current 3D display technology. The integrated imaging has high integration level of the film source image, so that the integrated imaging is utilized to encrypt the 3D image, and the encryption complexity and the ciphertext image data redundancy are reduced.
The principle of the encryption technology for computing ghost images is that plaintext information is encrypted into intensity information by utilizing second-order or higher-order correlation of a light field, and compared with the traditional optical image encryption, the encryption technology for computing the ciphertext information after ghost images is one-dimensional light intensity value, and the ciphertext storage space is greatly reduced. However, in practical applications, the computing of ghost image encryption requires a large number of speckle images, and the efficiency is extremely low if the speckle images are directly used as keys for data transmission.
Disclosure of Invention
In order to save the computational effort of a computer and simplify the encryption process when encrypting a 3D image, and improve the transmission efficiency while guaranteeing the security of a secret key, the application provides a 3D image encryption method based on computing ghost imaging.
The method mainly comprises the following steps:
firstly, recording a 3D object by utilizing integrated imaging to obtain a micro-image array EIA (Elemental Image Array), namely a plaintext;
step two, converting the obtained EIA into a corresponding binary image, and obtaining a series of two-dimensional random masks by using a cellular automaton coding technology, wherein the rules and initial parameters of the cellular automaton are key one;
thirdly, encrypting the plaintext EIA by calculating partial random masks generated by the ghost imaging technology and the cellular automaton to obtain a series of light intensity values, namely ciphertext, wherein the diffraction distance is a key II;
fourth, the correlation operation reconstruction, namely the decryption step, obtains the real light intensity distribution I of the EIA surface during encryption by using key operation r (x, y) and comparing it withCiphertext B r And (3) reconstructing by using an association algorithm to obtain the EIA, and then reconstructing by using integrated imaging to obtain the 3D image.
In the first step, namely, in the step of acquiring the EIA, a 3D image to be encrypted and the depth thereof are utilized, a 3D scene originally recorded is rendered and simulated through a reverse ray tracing technology, then the whole EIA image is traced and calculated, and the obtained EIA contains all three-dimensional information of a 3D object and is a plaintext object to be encrypted.
And in the second step, namely in the step of acquiring the random mask, the EIA is converted into a binary image, and the binary image is used as an initial mask to be input into a two-dimensional cellular automaton. At each subsequent time, the pixel value is outputIs determined by
Wherein the method comprises the steps ofRefers to the pixel value of the ith row, column, at time t, g (s 1 ,s 2 ,s 3 ,s 4 ,s 5 ) Is the selected rule. Thus, a total of N binary speckle patterns, i.e. random masks, satisfying the cellular automaton rules were obtained, where m, m+1, N random masks were taken for m+n (m+n.ltoreq.N)>Cellular automaton rules g(s) 1 ,s 2 ,s 3 ,s 4 ,s 5 ) And the initial parameter t is used as key one.
In the third step, in the step of calculating ghost image encryption, an optical path is designed, wherein the optical path comprises a laser light source, a beam expander, a Spatial Light Modulator (SLM) and a barrel detector. In the encryption process, laser passes through a spatial light modulator loaded with a random mask, and the modulation effect of the spatial light modulator on the optical field phase is as followsr represents the r-th measurement, and the reflected light field is represented asThe light beam freely propagates a distance z and irradiates on the plain text EIA, and the light field U reaching the EIA surface is formed by the light propagating in the space according to the Fresnel diffraction theory r (x, y, z) is not equal to the light field E projected by the spatial light modulator r (x, y, z=0), the light field distribution of the EIA front surface from the fresnel diffraction equation is:
where k is the wave vector of the light wave. The fresnel diffraction process can also be considered as a linear encryption operation, with the light field propagation distance z as key two. From the light field distribution, the theoretical value I of the light intensity of each point on the EIA surface can be calculated r (x,y,z)＝|U r (x,y,z)| 2 . The beam then passes through the EIA and the intensity B of the optical signal reflected by the EIA is collected by the drum detector r 。B r Calculated from the following formula:
B r ＝∫∫I r (x,y,z)T(x,y)dxdy (3)
where T (x, y) represents a plain image. In the process, the light intensity value B collected by the barrel detector r As ciphertext.
In the fourth step, in the decryption step, a series of random masks are obtained by utilizing the initial mask and the first secret key, namely, the two-dimensional cellular automaton rule and parameter operation, and the m to m+N random masks and the second secret key, namely, the propagation distance z are selected, so that the light intensity distribution I of the EIA surface can be calculated by utilizing the Fresnel diffraction formula r (x, y) and ciphertext B r And reconstructing by using a correlation algorithm to obtain an EIA image, wherein the correlation algorithm is as follows:
G(x,y)＝<I r (x,y)B r >-<I r (x,y)><B r > (4)
wherein < > represents ensemble averaging. The original plaintext image G (x, y) of the EIA can be reconstructed and decrypted, and then the original 3D image is reconstructed by the integrated imaging technology by utilizing the obtained EIA.
Drawings
The foregoing and advantages of the application may be further understood by reference to the following description taken in conjunction with the accompanying drawings, in which:
fig. 1 is a flow chart of encryption according to an embodiment of the present application.
FIG. 2 is a schematic diagram of simulated generation of an EIA for a ray tracing method according to an embodiment of the application.
Fig. 3 is a schematic diagram of a cellular automaton according to an embodiment of the application.
Fig. 4 is a diagram of an encryption system according to an embodiment of the present application.
It should be understood that the above-described figures are merely schematic and are not drawn to scale.
Detailed Description
In order to facilitate understanding of the present application, an exemplary embodiment of a 3D image encryption method based on computed ghost imaging according to the present application will be described in detail. It is to be noted herein that the embodiments described below are exemplary and are intended to further explain the present application and should not be construed as limiting the scope of the application.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in the description of the application herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the application. The term "and/or" as used herein includes any and all combinations of one or more of the associated listed items.
The use of the azimuthal terms "vertical," "horizontal," and similar expressions are used herein for illustrative purposes only and are not meant to be the only embodiment nor limiting of the application.
The following describes in detail a 3D image encryption method based on computed ghost imaging according to an embodiment of the present application and the accompanying drawings.
Fig. 4 shows a 3D image encryption method based on computed ghost imaging according to an embodiment of the present application, which includes the following steps.
In one embodiment, in the first step, in the step of obtaining the EIA, a 3D scene originally recorded is rendered and simulated by using a reverse ray tracing technology by using a 3D image to be encrypted and the depth thereof, so that the whole EIA image is traced and calculated, and the obtained EIA contains all three-dimensional information of the 3D object and is a plaintext object to be encrypted.
In one embodiment, in the second step, in the step of acquiring the random mask, the EIA is converted into a binary image, and the binary image is input as an initial mask into the two-dimensional cellular automaton. At each subsequent time, the pixel value is outputIs determined by
Wherein the method comprises the steps ofRefers to the pixel value of the ith row, column, at time t, g (s 1 ,s 2 ,s 3 ,s 4 ,s 5 ) Is the selected rule. Thus, a total of N binary speckle patterns, i.e. random masks, satisfying the cellular automaton rules were obtained, where m, m+1, N random masks were taken for m+n (m+n.ltoreq.N)>Cellular automaton rules g(s) 1 ,s 2 ,s 3 ,s 4 ,s 5 ) And the initial parameter t is used as key one.
In one embodiment, in the third step, in the step of computing ghost image encryption, an optical path is designed, the optical path including a laser source, a beam expander, a Spatial Light Modulator (SLM), and a barrel detector. Encrypted byIn the process, laser passes through a spatial light modulator loaded with a random mask, and the modulation effect of the spatial light modulator on the optical field phase is as followsr represents the r-th measurement, the light field after reflection is denoted +.>The light beam freely propagates a distance z and irradiates on the plain text EIA, and the light field U reaching the EIA surface is formed by the light propagating in the space according to the Fresnel diffraction theory r (x, y, z) is not equal to the light field E projected by the spatial light modulator r (x, y, z=0), the light field distribution of the EIA front surface from the fresnel diffraction equation is:
where k is the wave vector of the light wave. The fresnel diffraction process can also be considered as a linear encryption operation, with the light field propagation distance z as key two. From the light field distribution, the theoretical value I of the light intensity of each point on the EIA surface can be calculated r (x,y,z)＝|U r (x,y,z)| 2 . The beam then passes through the EIA and the intensity B of the optical signal reflected by the EIA is collected by the drum detector r 。B r Calculated from the following formula:
B r ＝∫∫I r (x,y,z)T(x,y)dxdy (3)
where T (x, y) represents a plain image. In the process, the light intensity value B collected by the barrel detector r As ciphertext.
In one embodiment, in the fourth step, in the decryption step, a series of random masks are obtained by using the initial mask and the first secret key, i.e. the two-dimensional cellular automaton rule and parameter operation, and the light intensity distribution I of the EIA surface can be calculated by using the Fresnel diffraction formula by selecting the m to m+N random masks and the second secret key, i.e. the propagation distance z r (x, y) and ciphertext B r And reconstructing by using a correlation algorithm to obtain an EIA image, wherein the correlation algorithm is as follows:
G(x,y)＝<I r (x,y)B r >-<I r (x,y)><B r > (4)
wherein < > represents ensemble averaging. The original image information G (x, y) of the EIA can be reconstructed and decrypted, and then the original 3D image is reconstructed by the integrated imaging technology by utilizing the obtained EIA.
Claims (5)
1. A3D image encryption method based on calculation ghost imaging is characterized in that: the method comprises the following steps:
s1: converting the 3D object into a micro-image array EIA (Element Image Array) by a reverse ray tracing technology to obtain a plaintext;
s2: converting the EIA obtained in S1 into a binary image, and inputting an operation rule intoThe cellular automaton encoding technique of (2) obtaining N two-dimensional random masks, taking the m < m+1 >, N random masks of m+n (m+n is less than or equal to N) total +.>Wherein->The pixel value at time t in row j is referred to as the cellular automaton rule g (s 1 ,s 2 ,s 3 ,s 4 ,s 5 ) The initial parameter t is used as a key one;
s3: designing an optical path comprising a laser light source, a beam expander, a Spatial Light Modulator (SLM) and a barrel detector, and generating a random mask by a cellular automatonLoaded on a spatial light modulator, the light field after reflection is +.>Wherein r represents the r-th measurement, E 0 For the light field emitted by the light source, the light beam passes through the EIA after freely traveling a distance z, and the light beam passes throughThe broadcasting process generates Fresnel diffraction, and the light field U is generated when the light reaches the front surface of the plaintext EIA r (x, y, z) can be calculated from the Fresnel diffraction equation and from I r (x,y,z)＝|U r (x,y,z)| 2 The operation can obtain the real light intensity distribution I of the EIA surface during encryption r (x, y, z) and then collecting the intensity of the optical signal passing through the EIA by the bucket detector, B r Is composed of B r ＝∫∫I r (x, y, z) T (x, y) dxdy is calculated by encryption, wherein T (x, y) represents a plaintext image, the diffraction distance z in the process is a key two, and B is collected by a barrel detector r For ciphertext, the light beam is sent to be encrypted into ciphertext B r The whole process of (1) is a ghost image calculating and encrypting step;
s4: correlation operation reconstruction, namely decryption, is carried out, a series of random masks are obtained by utilizing an initial mask and key one operation, and the light intensity distribution I of the EIA surface is obtained by utilizing the obtained m to m+N random masks, key two z and Fresnel diffraction formula r (x, y) and ciphertext B r Send-in association algorithm G (x, y) =<I r (x,y)B r >-<I r (x,y)><B r >Reconstructing to obtain EIA information G (x, y), wherein<>Representing ensemble averaging, and reconstructing by an integrated imaging technology to obtain an original 3D image.
2. The method for encrypting 3D images based on computed ghost imaging according to claim 1, wherein in the step S1, in the step of obtaining EIA, firstly, a 3D scene originally recorded is rendered and simulated by using a 3D image to be encrypted and the depth thereof through a reverse ray tracing technology, so that the whole EIA image is traced and computed, and the obtained EIA contains all three-dimensional information of the 3D object and is a plaintext object to be encrypted.
3. The method for encrypting 3D image based on computed ghost imaging according to claim 1, wherein in the step S2 of obtaining a random mask, firstly, the EIA obtained in the step S1 is converted into a binary image, and the binary image is input as an initial mask into a two-dimensional cellular automaton, and then, at each moment, the pixel value is outputIs determined by the following formula:
wherein the method comprises the steps ofRefers to the pixel value of the ith row, column, at time t, g (s 1 ,s 2 ,s 3 ,s 4 ,s 5 ) For the selected rule; thus, a total of N binary speckle patterns, i.e. random masks, satisfying the cellular automaton rules were obtained, where m, m+1, N random masks were taken for m+n (m+n.ltoreq.N)>Cellular automaton rules g(s) 1 ,s 2 ,s 3 ,s 4 ,s 5 ) And the initial parameter t is used as key one.
4. A method for encrypting a 3D image based on computed ghost image according to claim 1, wherein in step S3, in the step of encrypting the computed ghost image, the laser light passes through a spatial light modulator loaded with a random mask, and the modulation effect of the spatial light modulator on the phase of the light field is as followsr represents the r-th measurement, the light field after reflection is denoted +.>The light beam freely propagates a distance z and irradiates on the plain text EIA, and the light field U reaching the EIA surface is formed by the light propagating in the space according to the Fresnel diffraction theory r (x, y, z) is not equal to the light field E projected by the spatial light modulator r (x, y, z=0), the light field distribution of the EIA front surface from the fresnel diffraction equation is:
wherein k is a light wave vector, the Fresnel diffraction process can be regarded as a linear encryption operation, and the light field propagation distance z is taken as a key II; from the light field distribution, the theoretical value I of the light intensity of each point on the EIA surface can be calculated r (x,y,z)＝|U r (x,y,z)| 2 The beam then passes through the EIA and the intensity B of the optical signal reflected by the EIA is collected by the drum detector r ，B r Calculated from the following formula:
B r ＝∫∫I r (x,y,z)T(x,y)dxdy；
wherein T (x, y) represents a plain text image; in the process, the light intensity value B collected by the barrel detector r As ciphertext.
5. The 3D image encryption method based on computed ghost imaging according to claim 1, wherein in the step S4, in the decryption step, a series of random masks are obtained by using initial mask and key one-dimensional cellular automaton rules and parameter operations, and the light intensity distribution I of the EIA surface can be calculated by using fresnel diffraction formula by selecting the m to m+n-th random masks and key two-dimensional propagation distance z r (x, y) and ciphertext B r And reconstructing by using a correlation algorithm to obtain an EIA image, wherein the correlation algorithm is as follows:
G(x,y)＝<I r (x,y)B r >-<I r (x,y)><B r >；
wherein < > represents ensemble averaging; the original image information G (x, y) of the EIA can be reconstructed and decrypted, and then the original 3D image is reconstructed through integrated imaging by using the obtained EIA.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210662561.2A CN115065762B (en) | 2022-06-13 | 2022-06-13 | 3D image encryption method based on computing ghost imaging |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202210662561.2A CN115065762B (en) | 2022-06-13 | 2022-06-13 | 3D image encryption method based on computing ghost imaging |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN115065762A CN115065762A (en) | 2022-09-16 |
| CN115065762B true CN115065762B (en) | 2023-10-10 |
Family
ID=83200149
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202210662561.2A Active CN115065762B (en) | 2022-06-13 | 2022-06-13 | 3D image encryption method based on computing ghost imaging |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN115065762B (en) |
Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7043048B1 (en) * | 2000-06-01 | 2006-05-09 | Digimarc Corporation | Capturing and encoding unique user attributes in media signals |
| CN104284054A (en) * | 2014-08-05 | 2015-01-14 | 华北水利水电大学 | Multi-image encrypting and decrypting method based on ghost imaging and public key cryptography |
| CN106373082A (en) * | 2016-09-23 | 2017-02-01 | 中山大学 | Cellular automata and chaotic mapping-based digital image encryption method and decryption method thereof |
| CN107563179A (en) * | 2017-09-12 | 2018-01-09 | 山东大学 | The image authentication method shared based on the ghost imaging of row multiplexed compressed with hyperplane key |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US10848642B2 (en) * | 2013-04-18 | 2020-11-24 | Infineon Technologies Ag | Apparatus for generating trusted image data, an apparatus for authentication of an image and a method for generating trusted image data |
-
2022
- 2022-06-13 CN CN202210662561.2A patent/CN115065762B/en active Active
Patent Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7043048B1 (en) * | 2000-06-01 | 2006-05-09 | Digimarc Corporation | Capturing and encoding unique user attributes in media signals |
| CN104284054A (en) * | 2014-08-05 | 2015-01-14 | 华北水利水电大学 | Multi-image encrypting and decrypting method based on ghost imaging and public key cryptography |
| CN106373082A (en) * | 2016-09-23 | 2017-02-01 | 中山大学 | Cellular automata and chaotic mapping-based digital image encryption method and decryption method thereof |
| CN107563179A (en) * | 2017-09-12 | 2018-01-09 | 山东大学 | The image authentication method shared based on the ghost imaging of row multiplexed compressed with hyperplane key |
Non-Patent Citations (2)
| Title |
|---|
| 变换域混沌系统的图像加密;张志昌;《哈尔滨理工大学 硕士论文》;全文 * |
| 图像信息隐藏关键技术研究;泰克瑞;《中南大学博士论文》;全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN115065762A (en) | 2022-09-16 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Singh | Nonlinear optical double image encryption using random-optical vortex in fractional Hartley transform domain | |
| CN103117847B (en) | A kind of optical encryption method holographic based on chaos and calculating | |
| Wang et al. | Multiple-image encryption system using cascaded phase mask encoding and a modified Gerchberg–Saxton algorithm in gyrator domain | |
| Li et al. | Designing optical 3D images encryption and reconstruction using monospectral synthetic aperture integral imaging | |
| CN106408500A (en) | Image encryption and decryption method based on phase recovery algorithm and calculation correlated imaging | |
| Girija et al. | Triple-level cryptosystem using deterministic masks and modified Gerchberg-Saxton iterative algorithm in fractional Hartley domain by positioning singular value decomposition | |
| CN112989371B (en) | Multi-image encryption and decryption method based on Walsh transform and computational ghost imaging | |
| Chang et al. | Ciphertext-only attack on optical scanning cryptography | |
| Girija et al. | Security-enhanced optical nonlinear cryptosystem based on modified Gerchberg–Saxton iterative algorithm | |
| Liu et al. | Optical asymmetric JTC cryptosystem based on multiplication-division operation and RSA algorithm | |
| Li et al. | Multiple-3D-object secure information system based on phase shifting method and single interference | |
| CN115065762B (en) | 3D image encryption method based on computing ghost imaging | |
| Li et al. | Optical 3D object security and reconstruction using pixel-evaluated integral imaging algorithm | |
| CN116743934B (en) | Equal resolution image hiding and encrypting method based on deep learning and ghost imaging | |
| Chen et al. | Single-channel optical encryption of color image using chessboard grating and diffraction imaging scheme | |
| Han et al. | Three-dimensional scene encryption algorithm based on phase iteration algorithm of the angular-spectral domain | |
| Hu et al. | 1D Sine-Map-Coupling-Logistic-Map for 3D model encryption | |
| CN106530362A (en) | Calculating integral imaging technology and Fourier transform optical image encryption method | |
| Chatterjee et al. | Virtual optical encryption using phase shifted digital holography and RSA algorithm | |
| Li et al. | Hierarchical multilevel authentication system for multiple-image based on phase retrieval and basic vector operations | |
| CN109873814B (en) | Vortex laser array scanning holographic multi-image encryption system and method thereof | |
| Tsang et al. | Fast numerical generation and hybrid encryption of a computer-generated Fresnel holographic video sequence | |
| Wang et al. | Research on multiple-image encryption method using modified Gerchberg–Saxton algorithm and chaotic systems | |
| Li et al. | A virtual 3D object hiding scheme using logistic mapping chaos sequence | |
| Piao et al. | 3D image encryption based on computer-generated hologram |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |