CN110706145B - Reversible remote sensing image information hiding processing method and device - Google Patents
Reversible remote sensing image information hiding processing method and device Download PDFInfo
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Abstract
The embodiment of the invention discloses a reversible remote sensing image information hiding processing method and device, wherein the method comprises the following steps: preprocessing the remote sensing image after information completion by using sub-affine transformation scrambling to obtain a preprocessed image; performing two-dimensional DCT processing on the preprocessed image to obtain discrete cosine transform coefficients; and obtaining a target position with the discrete cosine transform coefficient as an intermediate frequency, and embedding information to be hidden into the target position to obtain a remote sensing image with the reversible information hidden. After sub-affine transformation scrambling and two-dimensional discrete cosine transformation processing are carried out on the remote sensing image, information to be hidden is embedded into a target position, so that the remote sensing image with hidden information is obtained, manual intervention is not needed, the information to be hidden in the remote sensing image can be hidden, the hidden information has good concealment, the embedded image can not be distinguished by naked eyes, the information safety is improved, and the expected information hiding effect is achieved; meanwhile, the method has good reversibility, and is convenient for subsequent restoration of the original image.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a reversible remote sensing image information hiding processing method and device.
Background
In order to improve the use benefit of the satellite, the information hiding technology can be utilized to realize hierarchical authorized use, namely, information is hidden to different degrees according to different authorities of users, so that the use efficiency of the satellite is improved. The information hiding technology is to hide secret information in another or separate and hide the secret information in common information on a plurality of surfaces by using the sensory redundancy of human sense organs to digital signals. The method is different from the traditional password system in that the content of the information is hidden and the existence of the information is hidden, and the method and the system can be matched in practical application, namely, the information is encrypted and then hidden, so that the method is a more effective method for guaranteeing the information security.
Information hiding in remote sensing images belongs to the "steganography" category of information hiding science. Steganography is an important branch of information hiding, studying how to hide confidential information. In view of the large difference and difference between the remote sensing image and the general image, the method has wide application prospect, so that the information hiding technology of the remote sensing image has important practical value and research significance.
The prior art generally adopts a simple blurring, mosaic adding or image self-disorder mode to carry out information hiding treatment, not only needs a large amount of manual intervention, but also can not automatically repair the defect part of the remote sensing image after confidential information is removed, and meanwhile, the adverse effect of 'three hundred and two silver without the ground' is caused, the hiding performance is poor, and the reversible remote sensing image information hiding treatment effect is far from the ideal effect.
Disclosure of Invention
Because the existing method has the problems, the embodiment of the invention provides a reversible remote sensing image information hiding processing method and device.
In a first aspect, an embodiment of the present invention provides a reversible remote sensing image information hiding method, including:
preprocessing the remote sensing image after information completion by using sub-affine transformation scrambling to obtain a preprocessed image;
performing two-dimensional Discrete Cosine Transform (DCT) processing on the preprocessed image to obtain discrete cosine transform coefficients;
and obtaining a target position with the discrete cosine transform coefficient of intermediate frequency, and embedding information to be hidden into the target position to obtain a remote sensing image with reversible information hidden.
Optionally, the obtaining the target position with the discrete cosine transform coefficient being the intermediate frequency, embedding the information to be hidden into the target position, and after obtaining the remote sensing image with the hidden information, further includes:
extracting hidden information from the remote sensing image with the hidden information according to the discrete cosine transform coefficient to obtain the information to be hidden;
and mapping the information to be hidden to obtain an intermediate image, and performing Amold transformation on the intermediate image according to the periodicity of the Amold transformation to obtain an original image.
Optionally, the performing two-dimensional discrete cosine transform DCT processing on the preprocessed image to obtain a discrete cosine transform coefficient specifically includes:
and performing block processing on the preprocessed image according to a preset size to obtain a plurality of pixel blocks, and performing two-dimensional DCT processing on the pixel blocks to obtain discrete cosine transform coefficients with the preset size.
Optionally, before performing the two-dimensional discrete cosine transform DCT processing on the preprocessed image to obtain the discrete cosine transform coefficient, the method further includes:
performing triple data encryption algorithm 3DES encryption on the preprocessed image to generate binary codes;
correspondingly, the performing two-dimensional Discrete Cosine Transform (DCT) processing on the preprocessed image to obtain discrete cosine transform coefficients specifically includes:
and performing two-dimensional Discrete Cosine Transform (DCT) processing on the binary codes to obtain discrete cosine transform coefficients.
In a second aspect, an embodiment of the present invention further provides a reversible remote sensing image information hiding processing device, including:
the preprocessing module is used for preprocessing the remote sensing image after information completion by adopting sub-affine transformation scrambling to obtain a preprocessed image;
the transformation processing module is used for carrying out two-dimensional Discrete Cosine Transform (DCT) processing on the preprocessed image to obtain discrete cosine transform coefficients;
and the information embedding module is used for acquiring a target position with the discrete cosine transform coefficient being intermediate frequency, and embedding information to be hidden into the target position to obtain a remote sensing image with reversible information hidden.
Optionally, the reversible remote sensing image information hiding processing device further includes:
the information extraction module is used for extracting hidden information of the remote sensing image after information hiding according to the discrete cosine transform coefficient to obtain the information to be hidden;
and the image recovery module is used for carrying out mapping processing on the information to be hidden to obtain an intermediate image, and carrying out Amold conversion on the intermediate image according to the periodicity of the Amold conversion to obtain an original image.
Optionally, the transformation processing module is specifically configured to:
and performing block processing on the preprocessed image according to a preset size to obtain a plurality of pixel blocks, and performing two-dimensional DCT processing on the pixel blocks to obtain discrete cosine transform coefficients with the preset size.
Optionally, the reversible remote sensing image information hiding processing device further includes:
the encryption processing module is used for carrying out triple data encryption algorithm (3 DES) encryption on the preprocessed image to generate a binary code;
correspondingly, the transformation processing module is specifically configured to:
and performing two-dimensional Discrete Cosine Transform (DCT) processing on the binary codes to obtain discrete cosine transform coefficients.
In a third aspect, an embodiment of the present invention further provides an electronic device, including:
at least one processor; and
at least one memory communicatively coupled to the processor, wherein:
the memory stores program instructions executable by the processor, which are called by the processor to perform the method described above.
In a fourth aspect, embodiments of the present invention also propose a non-transitory computer-readable storage medium storing a computer program, which causes the computer to carry out the above-mentioned method.
According to the technical scheme, after sub-affine transformation scrambling and two-dimensional discrete cosine transformation processing are carried out on the remote sensing image with the completed information, the information to be hidden is embedded into the target position, so that the reversible remote sensing image with the hidden information is obtained, manual intervention is not needed, the information to be hidden in the remote sensing image can be hidden, the hidden information has good concealment performance, the embedded image can not be distinguished by naked eyes, the information safety is improved, and the expected remote sensing image information hiding effect is achieved; meanwhile, the method has good reversibility, and is convenient for subsequent restoration of the original image.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions of the prior art, the drawings that are necessary for the description of the embodiments or the prior art will be briefly described, it being obvious that the drawings in the following description are only some embodiments of the invention and that other drawings can be obtained from these drawings without inventive effort for a person skilled in the art.
Fig. 1 is a schematic flow chart of a reversible remote sensing image information hiding method according to an embodiment of the present invention;
FIG. 2 is a flowchart illustrating a DCT-based information hiding process according to an embodiment of the present invention;
FIG. 3 is a flowchart illustrating a DCT-based information extraction process according to one embodiment of the present invention;
fig. 4 is a schematic flow chart of a reversible remote sensing image information hiding method according to another embodiment of the present invention;
fig. 5 is a schematic structural diagram of a reversible remote sensing image information hiding device according to an embodiment of the present invention;
fig. 6 is a logic block diagram of an electronic device according to an embodiment of the present invention.
Detailed Description
The following describes the embodiments of the present invention further with reference to the accompanying drawings. The following examples are only for more clearly illustrating the technical aspects of the present invention, and are not intended to limit the scope of the present invention.
Fig. 1 shows a flow chart of a reversible remote sensing image information hiding processing method provided in this embodiment, including:
s101, preprocessing the remote sensing image after information completion by using sub-affine transformation scrambling to obtain a preprocessed image.
Wherein the sub-affine transformation scrambling is a method of preprocessing an image, specifically: for a given N-order digital image, a= { m (i, j } n×n, if there is a transform:
where a, b, c, d, e, f are integers and have x, y e {1,2,.., N }, and satisfying that the transformation is a discrete point domain { (x, y): 1.ltoreq.x.ltoreq.N, 1.ltoreq.y.ltoreq.N and is an integer, the mapping is called sub-affine transformation of the digital image. The image safety can be ensured by preprocessing the sub-affine transformation scrambling of the sensitive area image.
S102, performing two-dimensional DCT (discrete cosine transform ) processing on the preprocessed image to obtain discrete cosine transform coefficients.
The DCT is an information hiding algorithm, and compared with the LSB information hiding algorithm, the DCT has better robustness for embedding information in the frequency domain of the signal, and can better resist attacks such as cutting, compression and the like. According to the mathematical theorem, a continuous real symmetric function meeting the condition in the Di Li He in any given interval can be expanded into a Fourier series only containing cosine terms, when information is hidden, an image can be expanded into a symmetric function, and if one image element is overlapped to be folded into a symmetric form, the transformation obtained by the expansion method is an odd discrete cosine transformation; the variation resulting from this extension method is an even discrete cosine transform if it is folded into a symmetrical form around the image boundary. The two-dimensional even Discrete Cosine Transform (DCT) is defined as:
u＝0，1，2，...，M-1；
v＝0，1，2，...，N-1
x＝0，1，2，...，M-1；
y＝0，1，2，...，N-1
wherein:
thus, it is possible to obtain:
s103, obtaining a target position with a discrete cosine transform coefficient of intermediate frequency, and embedding information to be hidden into the target position to obtain a remote sensing image with reversible information hidden.
Specifically, after the discrete cosine transform coefficients are arranged in the order of Zig-Zag from low frequency to high frequency, the high frequency portion represents noise in the image, the middle and low frequencies represent most of energy in the image, including important information that acts on human vision, and the change of the low frequency portion can cause large variation of the image, so that hidden information is generally embedded in the middle frequency portion (target position) of the image signal, so that visual transformation is not caused, and the image signal is not destroyed.
The improved LSB algorithm is adopted for feature region image embedding and hiding, the basic idea of the algorithm is to embed the encrypted feature region image information into the lowest position of RGB of the completed image, the selection of the embedded position is selected according to the SIFT method, namely, the information is embedded into the region with unchanged SIFT, and the geometric attack resistance of the image embedding method is improved. Because the embedding is performed at the least significant bit of RGB, the difference between the image and the completed image is not recognized by human eyes, so that the aim of hiding the sensitive information can be achieved.
For a Bmp image, since the Bmp image is lossless, each pixel represents pixels of three red, green, and blue channels with three values of 0-255, a Least Significant Bit (LSB) algorithm can be used for information hiding. And sequentially writing the information to be embedded into the least significant bit of the Bmp pixel to achieve the purpose of embedding. The biggest advantage of the algorithm is the embedding capacity, and the parameter setting in the tool determines that the information of 6bpp (bit per pixel) can be hidden in one Bmp image, so that the binary string generated in the encryption process can be hidden.
Taking a gray image as an example, the LSB algorithm is briefly introduced: for simple algorithmic analysis, taking a gray image as an example, each pixel represents the depth of black and white color with 0-255, the host image is represented as a gray image, the image to be hidden is represented as a binary image, black with 0 and white with 1. The lowest bit of each pixel point of the host image is obtained, the lowest bit is exclusive-or' ed with the binary image, the result is unchanged if the result is 0, the result is 1, the lowest bit of the host image is 1, the result is 0, and the result is 1 if the lowest bit of the host image is 0. The algorithm must ensure that the size of the host image is larger than the image to be hidden. The pixel transformation of the whole image is invisible to naked eyes because only the lowest bit of the host image is changed, so that the method can be used for information hiding.
For the JPEG image, the JPEG image is subjected to DCT conversion, so that the information can not be hidden by using an LSB algorithm, a conversion domain algorithm is used, DCT conversion parameters of image blocks are used as an embedded carrier, but the information capacity is greatly reduced compared with LSB, and the problem of insufficient embedded capacity is possibly caused by about 1/32 bpp.
After the completed image is obtained, sensitive information is hidden in the completed image, and the sensitive information can be recovered by a certain means, which is a serious problem of the project, wherein the main used technology is a digital watermarking technology. In combination with the invocation of the digital watermarking technology, the embodiment selects an image embedding method resistant to geometric attacks, and the method mainly comprises three steps: scrambling preprocessing, DES encryption, and information hiding against geometric attacks.
According to the embodiment, after sub-affine transformation scrambling and two-dimensional discrete cosine transformation processing are carried out on the remote sensing image with the fully-filled information, the information to be hidden is embedded into the target position, so that the remote sensing image with the reversibly-hidden information is obtained, manual intervention is not needed, the information to be hidden in the remote sensing image can be hidden, the remote sensing image has good concealment, the embedded image can not be distinguished by naked eyes, the information safety is improved, and the expected remote sensing image information concealment effect is achieved; meanwhile, the method has good reversibility, and is convenient for subsequent restoration of the original image.
Further, on the basis of the above method embodiment, after S103, the method further includes:
s104, extracting hidden information of the remote sensing image with the hidden information according to the discrete cosine transform coefficient to obtain the information to be hidden.
S105, mapping the information to be hidden to obtain an intermediate image, and performing Amold transformation on the intermediate image according to the periodicity of the Amold transformation to obtain an original image.
Specifically, as shown in fig. 2, the information hiding flow based on the DCT coefficients specifically includes the following steps:
(1) And carrying out Amold scrambling on the host image A, and obtaining an image B after carrying out n times of iterative scrambling on the host image, wherein the scrambling period is assumed to be T.
(2) The following is done for image B:
(3) Sequentially embedding elements in F into the selected DCT coefficients, wherein the embedding formula is as follows:
Y(i,j)＝X(i,j)*(1+F(m,n)*α)
wherein α represents the embedding strength, and the correspondence between the position information (i, j) and (m, n) is determined in the process of selecting the embedding position, so as to achieve the optimal embedding effect.
(4) After the processing, each image block is subjected to fine discrete cosine inverse transformation to obtain a reconstructed image with hidden information.
Accordingly, the DCT-based information extraction flow is shown in fig. 3, and specifically includes the following steps:
(1) Dividing the image embedded with hidden information into 8×8 small blocks, performing discrete cosine DCT to obtain coefficient values, and using formula
And extracting hidden information.
(2) The F element is subjected to reflection processing, and the formula is
(3) And finally, carrying out T-T times of Amold transformation on E by utilizing the periodicity of Amold transformation, and reconstructing an image.
The main objective of information hiding is to transmit secret information hidden in a disguised carrier, and an unknowing third party cannot perceive the existence of the hidden information. Of the three main characteristics of imperceptibility, capacity and robustness of information hiding, steganography emphasizes imperceptibility and capacity even more, while digital watermarking emphasizes robustness even more. In steganography, imperceptibility occupies the first place, and the capacity of the secret which can be embedded is required to be large, so that an optimal balance point needs to be found among the three; information hiding is typically dependent on the type of embedded carrier. The carriers used are all carriers based on images. In the application process of the information hiding technology, if the secret information is hidden and kept secret only by using various information hiding algorithms, an attacker can extract the secret information only by directly using various existing information extraction algorithms to carry out exhaustive operation on the intercepted information. However, if we first process the secret information according to a certain operation rule before hiding the information, so that the secret information loses its original purpose, and then hides the secret information into the carrier information, so that the secret information to be transmitted is safer. Even if an attacker extracts the secret information from the carrier, it cannot be distinguished what is hidden by the preprocessed secret information, and thus the extraction/detection algorithm is considered to be wrong or the carrier does not contain any other information. Therefore, preprocessing of secret information is necessary. This is also an important direction of our information hiding technology research in the future. That is, in the preprocessing stage, various schemes are adopted to process the secret information and the carrier, so that the hidden information achieves the first layer of security.
The information hiding technology can scramble and encrypt confidential information such as images, voices or words, and then hide the information in a publicly available carrier image, so that others cannot perceive the existence of secrets, and the existing image scrambling and encrypting technology is realized: arnold transformation, hilbert curve transformation, fibonacci transformation, magic square transformation, FASS curve, fractal technique, orthogonal Latin square, rider tour, affine transformation, primitive root, scrambling method of Gray code transformation, etc. The scrambling of the digital image is reversible transformation, and the scrambling is to disturb the color, the position and the frequency of the digital image on a two-dimensional level so that the scrambled image is disordered, and if the scrambling type is not known, the image is difficult to recover. Digital image scrambling may be performed in the spatial domain of the digital image, e.g., color space, position space, or in the frequency domain of the digital image.
Further, on the basis of the above method embodiment, S102 specifically includes:
and performing block processing on the preprocessed image according to a preset size to obtain a plurality of pixel blocks, and performing two-dimensional DCT processing on the pixel blocks to obtain discrete cosine transform coefficients with the preset size.
Specifically, the preprocessed image is first divided into 8×8 pixel blocks, and then two-dimensional DCT transform is performed to obtain 8×8 discrete cosine transform coefficients, which are arranged in the order of Zig-Zag from low frequency to high frequency. In the DCT coefficients, the high frequency part represents noise in the image, the middle and low frequencies represent most of the energy in the image, including important information contributing to human vision, and changes in the low frequency part can cause large variations in the image, so that hidden information is generally embedded in the middle frequency part of the image signal, so that visual transformation is not caused, and the image signal is not destroyed.
Further, on the basis of the above method embodiment, before S102, the method further includes:
s1012, performing triple data encryption algorithm 3DES encryption on the preprocessed image to generate binary codes;
correspondingly, S102 specifically includes:
and performing two-dimensional Discrete Cosine Transform (DCT) processing on the binary codes to obtain discrete cosine transform coefficients.
Specifically, DES algorithm 1974 was proposed by IBM, and 1977 is a national standard which has been used up to date and has a strong vitality. The original DES algorithm supports a key length of 8 bytes, where a simple extension is made, supporting a maximum of 16 bytes of cipher. In cryptography, a Triple data encryption algorithm (Triple Data Encryption Algorithm, abbreviated as TDEA, triple DEA), or 3DES (Triple DES), is a symmetric key encryption block cipher, which is equivalent to applying a Triple Data Encryption Standard (DES) algorithm to each data block. Due to the enhancement of the computing capability of the computer, the key length of the original edition DES password becomes easy to be cracked by violence; rather than designing a completely new block cipher algorithm, 3DES is designed to provide a relatively simple method of avoiding similar attacks by increasing the key length of DES. When the password set by the user is more than 8 bytes, the first 8 bytes are used for encryption twice, and the second 8 bytes are used for encryption between the two times, namely three times of encryption are performed in total, so that the safety performance is ensured.
In this embodiment, 3DES encryption is performed on the scrambled image information according to the key, and a binary code containing the image information of the sensitive area is generated as an input for hiding the next step mainly for the key area by using 3DES encryption, specifically, the binary code has the following format: rectangular coordinates of the key area + pixel values of the key area rectangle. Rectangular coordinates store 4-byte integers in top, bottom, left, right order, and the subsequent key region rectangle is stored as a file named tmp. Jpg, and the file contents are sequentially written into the binary string, which can reduce the amount of embedded information, which is then deleted.
The decryption process is contrary to the encryption process described above, where the rectangles of the key areas and subsequent jpeg image content are extracted to recover the original image. If any step finds that the parameters are unreasonable, the input image is not provided with a hidden area or password setting error.
The reversible remote sensing image information hiding processing method provided by the embodiment is as shown in fig. 4, firstly, sensitive or secret content in an image is extracted in a quick interaction manner, and then, a cavity generated after information extraction is repaired by using an image complement method, so that the removal of the sensitive content is realized; meanwhile, the sensitive image content is hidden into the whole image through a hiding algorithm, so that the safety of information is improved; and finally, recovering the hidden information by using the secret key to obtain an original image.
The operating system platform for the remote sensing image information hiding and repairing software platform is Windows 7-bit operating system and above, and the functions of the software are introduced from the two aspects of functional modules and war technical index requirements of the software platform. The software functional design is shown in the following table:
the software index function design is shown in the following table:
the embodiment adopts modular and expandable MVC componentization software programming, and provides a system platform based on a Windows operating system. The software platform is easy to operate and easy to operate, and the main flow comprises a hiding flow and an extracting flow.
The hiding flow comprises the following steps:
1) Opening the original image through an "open" option in a "file" menu or an "open" button in a toolbar; after the original image is opened, the loaded image may be subjected to an "up" or "down" operation.
2) Setting a key area through a 'set key area' option in a 'hidden' menu or a 'set key area' button in a toolbar; the software platform supports the adjustment of the size of the brush, the brush can be enlarged to realize quick coating by pressing the L key, and the brush can be reduced to realize fine coating by pressing the K key. Meanwhile, the application mode supports two modes of 'pen brushing and wiping' and 'boundary line setting'.
3) In the setting process of the key area, a left button of a mouse is used for clicking in the image, the points are sequentially used as polygon boundary points, and right buttons are clicked at any positions to automatically close the polygons, so that a closed polygon area is formed as the key area.
4) By "understanding key region" option in "hide" menu, or "understanding key region" button in toolbar, try to draw out the fuzzy filling effect of key region, if its result is satisfactory, go to step 5, otherwise return to step 3.
5) By hiding the "refine key region" option in the menu or the "refine key region" button in the toolbar, refining the result of preliminary filling the key region in step 4, this step consumes a relatively long time and requires a tolerance waiting.
6) At any time after the file is opened, the hidden password can be set through a password setting option in a file menu or a password setting button in a toolbar.
7) The key areas that are mined are hidden in the mined image in the form of watermarks by the "execute hide" option in the "hide" menu, or the "execute hide" button in the toolbar.
8) And saving the currently displayed image to a disk through a save option in a file menu or a save button in a toolbar, so that the hiding flow is finished.
The extraction process comprises the following steps:
1) The image with the hidden local information is opened by an "open" option in the "File" menu, or an "open" button in the toolbar.
2) The password setting option in the file menu or the password setting button in the toolbar sets the extraction password, and the password is the same as the password set in hiding, otherwise, the local information cannot be extracted.
3) The extraction process is completed through the extraction executing option in the extraction menu or the extraction executing button in the toolbar, after the extraction is successful, the local area is restored, and the extraction flow is ended.
The image information embedding and hiding method provided by the embodiment is to process the sensitive information and then embed the sensitive information into the image, but the embedded image has no perceivable difference in human eyes compared with the original image, so that the purposes of hiding the information in the image and extracting and reproducing the information through a certain means are achieved. The implementation provides a reversible image hiding and restoring method, so that the image can be completely restored after the information is embedded.
Fig. 5 shows a schematic structural diagram of a reversible remote sensing image information hiding processing device provided in this embodiment, where the device includes: a preprocessing module 501, a transformation processing module 502, and an information embedding module 503, wherein:
the preprocessing module 501 is configured to preprocess the remote sensing image after information completion by using affine transformation scrambling to obtain a preprocessed image;
the transformation processing module 502 is configured to perform two-dimensional discrete cosine transform DCT processing on the preprocessed image to obtain a discrete cosine transform coefficient;
the information embedding module 503 is configured to obtain a target position with a discrete cosine transform coefficient being an intermediate frequency, and embed information to be hidden into the target position, so as to obtain a remote sensing image with reversible information hidden.
Specifically, the preprocessing module 501 performs preprocessing on the remote sensing image after information completion by using affine transformation scrambling to obtain a preprocessed image; the transformation processing module 502 performs two-dimensional Discrete Cosine Transform (DCT) processing on the preprocessed image to obtain discrete cosine transform coefficients; the information embedding module 503 obtains a target position with a discrete cosine transform coefficient being an intermediate frequency, and embeds information to be hidden into the target position, so as to obtain a remote sensing image with reversible information hidden.
According to the embodiment, after sub-affine transformation scrambling and two-dimensional discrete cosine transformation processing are carried out on the remote sensing image with the fully-filled information, the information to be hidden is embedded into the target position, so that the remote sensing image with the reversibly-hidden information is obtained, manual intervention is not needed, the information to be hidden in the remote sensing image can be hidden, the remote sensing image has good concealment, the embedded image can not be distinguished by naked eyes, the information safety is improved, and the expected remote sensing image information concealment effect is achieved; meanwhile, the method has good reversibility, and is convenient for subsequent restoration of the original image.
Further, on the basis of the above device embodiment, the reversible remote sensing image information hiding processing device further includes:
the information extraction module is used for extracting hidden information of the remote sensing image after information hiding according to the discrete cosine transform coefficient to obtain the information to be hidden;
and the image recovery module is used for carrying out mapping processing on the information to be hidden to obtain an intermediate image, and carrying out Amold conversion on the intermediate image according to the periodicity of the Amold conversion to obtain an original image.
Further, on the basis of the above device embodiment, the transformation processing module is specifically configured to:
and performing block processing on the preprocessed image according to a preset size to obtain a plurality of pixel blocks, and performing two-dimensional DCT processing on the pixel blocks to obtain discrete cosine transform coefficients with the preset size.
Further, on the basis of the above device embodiment, the reversible remote sensing image information hiding processing device further includes:
the encryption processing module is used for carrying out triple data encryption algorithm (3 DES) encryption on the preprocessed image to generate a binary code;
correspondingly, the transformation processing module is specifically configured to:
and performing two-dimensional Discrete Cosine Transform (DCT) processing on the binary codes to obtain discrete cosine transform coefficients.
The reversible remote sensing image information hiding processing device in this embodiment may be used to execute the above method embodiments, and the principle and technical effects are similar, and are not described herein again.
Referring to fig. 6, the electronic device includes: a processor (processor) 601, a memory (memory) 602, and a bus 603;
wherein,,
the processor 601 and the memory 602 perform communication with each other through the bus 603;
the processor 601 is configured to invoke program instructions in the memory 602 to perform the methods provided by the method embodiments described above.
The present embodiments disclose a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, are capable of performing the methods provided by the method embodiments described above.
The present embodiment provides a non-transitory computer-readable storage medium storing computer instructions that cause a computer to perform the methods provided by the above-described method embodiments.
The apparatus embodiments described above are merely illustrative, wherein the elements illustrated as separate elements may or may not be physically separate, and the elements shown as elements may or may not be physical elements, may be located in one place, or may be distributed over a plurality of network elements. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art will understand and implement the present invention without undue burden.
From the above description of the embodiments, it will be apparent to those skilled in the art that the embodiments may be implemented by means of software plus necessary general hardware platforms, or of course may be implemented by means of hardware. Based on this understanding, the foregoing technical solution may be embodied essentially or in a part contributing to the prior art in the form of a software product, which may be stored in a computer readable storage medium, such as ROM/RAM, a magnetic disk, an optical disk, etc., including several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the method described in the respective embodiments or some parts of the embodiments.
It should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and are not limiting; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present invention.
Claims (8)
1. A reversible remote sensing image information hiding processing method is characterized by comprising the following steps:
preprocessing the remote sensing image after information completion by using sub-affine transformation scrambling to obtain a preprocessed image;
performing two-dimensional Discrete Cosine Transform (DCT) processing on the preprocessed image to obtain discrete cosine transform coefficients;
obtaining a target position with a discrete cosine transform coefficient of intermediate frequency, and embedding information to be hidden into the target position to obtain a remote sensing image with reversible information hidden;
wherein, before performing two-dimensional Discrete Cosine Transform (DCT) processing on the preprocessed image to obtain discrete cosine transform coefficients, the method further comprises:
performing triple data encryption algorithm 3DES encryption on the preprocessed image to generate binary codes;
correspondingly, the performing two-dimensional Discrete Cosine Transform (DCT) processing on the preprocessed image to obtain discrete cosine transform coefficients specifically includes:
and performing two-dimensional Discrete Cosine Transform (DCT) processing on the binary codes to obtain discrete cosine transform coefficients.
2. The method for hiding reversible remote sensing image information according to claim 1, wherein the steps of obtaining a target position with a discrete cosine transform coefficient being an intermediate frequency, embedding information to be hidden into the target position, and obtaining the reversible remote sensing image after hiding the information further comprise:
extracting hidden information from the remote sensing image with the hidden information according to the discrete cosine transform coefficient to obtain the information to be hidden;
and mapping the information to be hidden to obtain an intermediate image, and performing Amold transformation on the intermediate image according to the periodicity of the Amold transformation to obtain an original image.
3. The reversible remote sensing image information hiding method according to claim 1, wherein said performing two-dimensional discrete cosine transform DCT on said preprocessed image to obtain discrete cosine transform coefficients, specifically comprises:
and performing block processing on the preprocessed image according to a preset size to obtain a plurality of pixel blocks, and performing two-dimensional DCT processing on the pixel blocks to obtain discrete cosine transform coefficients with the preset size.
4. A reversible remote sensing image information hiding processing device, characterized by comprising:
the preprocessing module is used for preprocessing the remote sensing image after information completion by adopting sub-affine transformation scrambling to obtain a preprocessed image;
the transformation processing module is used for carrying out two-dimensional Discrete Cosine Transform (DCT) processing on the preprocessed image to obtain discrete cosine transform coefficients;
the information embedding module is used for acquiring a target position with a discrete cosine transform coefficient of intermediate frequency, embedding information to be hidden into the target position and obtaining a remote sensing image with reversible information hidden;
the reversible remote sensing image information hiding processing device further comprises:
the encryption processing module is used for carrying out triple data encryption algorithm (3 DES) encryption on the preprocessed image to generate a binary code;
correspondingly, the transformation processing module is specifically configured to:
and performing two-dimensional Discrete Cosine Transform (DCT) processing on the binary codes to obtain discrete cosine transform coefficients.
5. The reversible remote sensing image information hiding processing apparatus according to claim 4, further comprising:
the information extraction module is used for extracting hidden information of the remote sensing image after information hiding according to the discrete cosine transform coefficient to obtain the information to be hidden;
and the image recovery module is used for carrying out mapping processing on the information to be hidden to obtain an intermediate image, and carrying out Amold conversion on the intermediate image according to the periodicity of the Amold conversion to obtain an original image.
6. The reversible remote sensing image information hiding processing device according to claim 4, wherein the transformation processing module is specifically configured to:
and performing block processing on the preprocessed image according to a preset size to obtain a plurality of pixel blocks, and performing two-dimensional DCT processing on the pixel blocks to obtain discrete cosine transform coefficients with the preset size.
7. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor implements the reversible remote sensing image information hiding method of any one of claims 1 to 3 when the program is executed by the processor.
8. A non-transitory computer readable storage medium having stored thereon a computer program, wherein the computer program when executed by a processor implements the reversible remote sensing image information hiding method according to any one of claims 1 to 3.
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