CN111708176A - Self-adaptive heterogeneous variable resolution ghost imaging method and system - Google Patents
Self-adaptive heterogeneous variable resolution ghost imaging method and system Download PDFInfo
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Abstract
The invention discloses a self-adaptive heterogeneous variable resolution ghost imaging method and a system, and belongs to the technical field of optical imaging. The implementation method of the invention comprises the following steps: the method comprises the steps of carrying out image processing according to a first ghost imaging result, detecting a circular area where a target object is located through image processing by using priori knowledge, determining the position of the circle center of the circular area to generate non-uniform speckles with adjustable resolution corresponding to the position and the size, projecting the non-uniform speckles to a target to carry out secondary imaging, carrying out area division, recombination and pixel filling of a random matrix on classical speckles under a polar coordinate to realize generation of the non-uniform speckles, namely, carrying out self-adaptive adjustment on the position of a high-resolution central point according to actual condition requirements, carrying out high-resolution speckle imaging on an induction area, carrying out low-resolution speckle imaging on a non-induction area, reducing data volume and further improving ghost imaging efficiency. The invention also discloses a self-adaptive heterogeneous variable resolution ghost imaging system for realizing the method.
Description
Technical Field
The invention belongs to the technical field of optical imaging, and particularly relates to a self-adaptive heterogeneous variable resolution ghost imaging method and system.
Background
Ghost imaging is a novel imaging technology for recovering scene information to be detected by utilizing the light field intensity correlation characteristic. Unlike the direct imaging of the traditional area array detector, the ghost imaging only utilizes a single-point detector without spatial resolution, and the reconstruction of the target scene information can be realized by correlating the fluctuation of the light field and the total light intensity change of the echo. Due to the advantages of high detection efficiency, low noise, low cost, simple structure and the like, ghost imaging shows huge application prospects in the fields of space remote sensing, optical encryption transmission, medical imaging and the like.
The method is a system for indirectly imaging a target by means of a detection arm and a reference arm, wherein the detection arm is a point detector, the reference arm adopts an array detector, and most of the reference arm adopts a (high-resolution) array detector. At present, ghost imaging can be realized by two modes, namely a classical mode and a calculation mode. The classical ghost imaging obtains the optical field fluctuation of the reference arm through pseudo-thermal light and a high-resolution camera, the computed ghost imaging is modulated by adopting space light, such as a space modulator and a digital micromirror array device, and the computed ghost imaging structure is simpler, and the corresponding rate of the digital micromirror array device is higher (up to 22kHz), so that the computed ghost imaging method becomes a mainstream method and a research hotspot for implementing the ghost imaging in recent years. However, in the case of the computational ghost imaging using the digital micromirror array device, since the pixels have only "0" and "1" states, and the real scene has gray scale information or color information, the digital micromirror array not only needs to simulate the projected speckle having the gray scale information, but also needs to restore the scene information through multiple spectra, which undoubtedly reduces the effective operating frequency of the digital micromirror array device. Especially in large field of view, high resolution imaging, leading to further reduction in real-time.
In recent years, although ghost imaging methods based on compressed sensing, iterative optimization algorithm, deep learning and the like are proposed successively, the problem of low-efficiency speckle projection under a large field of view and high-resolution condition is still difficult to solve.
Disclosure of Invention
In order to solve the problem that in practical application of the traditional ghost imaging, in the face of the problem that an interested target in a large field of view is small and the imaging speed is low due to the fact that the resolution ratio is fixed and cannot be adjusted, the invention discloses a self-adaptive heterogeneous variable resolution ghost imaging method and system, which aim to solve the technical problems that: the method comprises the steps of carrying out image processing according to a first ghost imaging result, detecting a circular area where a target object is located through image processing by using priori knowledge, generating nonuniform speckles with adjustable resolution corresponding to the position and the size through determining the position of the circle center of the circular area, projecting the nonuniform speckles to a target for secondary imaging, carrying out area division, recombination and pixel filling of a random matrix on classical speckles under a polar coordinate to realize generation of the nonuniform speckles, namely, carrying out self-adaptive adjustment on the position of a high-resolution central point according to actual condition requirements, carrying out high-resolution speckle imaging on an induction area, carrying out low-resolution speckle imaging on a non-induction area, reducing data volume and further improving ghost imaging efficiency.
The invention is realized by the following technical scheme.
The invention discloses a self-adaptive heterogeneous variable resolution ghost imaging method, which comprises the following steps:
step one, initializing ghost imaging parameter configuration.
Initially configured ghost imaging parameters include high resolution region radius r0, resolution m, maximum discrete angle P, maximum discrete loop number Q.
And secondly, loading initial non-uniform annular speckles through a digital micro-mirror array device according to the initialization parameters, projecting the initial non-uniform annular speckles onto a target object through a tube laser, and performing correlation calculation on speckle light intensity signals received by a single-point detector and corresponding light intensity signals reflected by the target object to realize image reconstruction so as to complete primary speckle projection, ghost imaging sampling and image reconstruction.
The second step is realized by the following concrete method: the speckle light intensity signal Si received by the single-point detector and the light intensity signal Yi reflected by the corresponding target object.
Ti＝<Si·Yi>-<Si><Yi>
< > represents the statistical mean value, and Ti represents the reconstructed object.
Preferably, the laser is preferably a diode laser.
And step three, determining the circle center position of the adaptive speckles and the radius of the high-resolution area by using priori knowledge, and performing area division, recombination and pixel filling of a random matrix on the classical speckles under a polar coordinate, namely, generating the non-uniform speckles with the adaptive adjustment resolution corresponding to the positions and the sizes in a heterogeneous mode.
The step 3.1 of determining the circle center position of the adaptive speckle and the radius of the high-resolution area comprises an automatic method or a manual method.
The automatic method for determining the circle center position of the adaptive speckle and the radius of the high-resolution area comprises the following steps: and (3) extracting a target from the image information obtained in the step (II) by using the type of the interested object set in advance through an image processing algorithm, detecting a circular area where the target object is located, determining the position of the circle center of the circular area and the radius of a high-resolution area, improving the resolution to a target parameter, resetting the maximum value P 'of the discrete angle and the maximum value Q' of the discrete ring number.
The position of the high-resolution center point is adaptively adjusted according to actual situation requirements: and judging whether the target central area resolution is the set high-resolution area resolution or not. If the resolution is a numerical value set by the high-resolution area, the center position of the area of interest is an initial set circle center coordinate (x0, y 0); if the value is not equal to the value set by the high-resolution area, the target central area is reselected as the speckle high-resolution area, and the circle center coordinates are determined (x0, y 0).
Setting the radius of the central area: and obtaining a circumscribed circle of the target object by using an image processing algorithm, determining the maximum distance r0 'between the coordinates of the central point and the outside, and changing r0 into r 0'.
The implementation method for determining the circle center position of the adaptive speckle and the radius of the high-resolution area by a manual method comprises the following steps: manually selecting the circle center position of the interested region, adaptively adjusting the position of the high-resolution center point according to the actual condition requirement, setting the circle center coordinates (x0, y0) and the radius r0 ' of the high-resolution region, resetting the maximum value P ' of the discrete angle and the maximum value Q ' of the discrete ring number, and improving the resolution to the target parameter.
And 3.2, utilizing the circle center position, the high-resolution area radius, the resolution, the maximum value P 'of the discrete angle and the maximum value Q' of the discrete ring number obtained by an automatic or manual method, and realizing the generation of the non-uniform speckles by carrying out area division, recombination and pixel filling of a random matrix on the classical speckles under a polar coordinate, namely, the non-uniform speckles with self-adaptive resolution regulation corresponding to the positions and sizes of heterogeneous generation.
Step four: and projecting the non-uniform speckles with self-adaptive resolution adjustment corresponding to the positions and sizes of the three heterogeneous generation steps, performing correlation calculation on the obtained reflected light intensity signals and the emitted speckle light intensity, performing high-resolution speckle imaging on the induction area, and performing low-resolution speckle imaging on the non-induction area, thereby completing overall image reconstruction, reducing data volume and further improving ghost imaging efficiency.
The implementation method of the fourth step is as follows: and projecting the non-uniform speckles with self-adaptive resolution adjustment corresponding to the positions and sizes of the three heterogeneous generation steps, performing correlation calculation on the obtained reflected light intensity signals and the emitted speckle light intensity, performing high-resolution speckle imaging on the induction area, and performing low-resolution speckle imaging on the non-induction area, thereby completing overall image reconstruction, reducing data volume and further improving ghost imaging efficiency.
Preferably, before the three-step speckle generation submodule operates, the number of speckle projections is reduced by adding the compressed sensing submodule to reach the Nyquist sampling number, the sampling time is reduced, the imaging quality is not damaged, and the imaging efficiency is improved.
Preferably, a deep learning submodule is added after the associated imaging submodule in the step four runs, and the low-resolution image is trained in advance through the deep learning submodule to achieve the purpose of predicting the image after the resolution is improved according to the low-resolution image, so that the high-resolution image reconstruction is realized under the condition of lower projection speckle number, the speckle projection number is effectively reduced, and the ghost imaging efficiency is improved.
The invention also discloses a self-adaptive heterogeneous variable resolution ghost imaging system which is used for realizing the self-adaptive heterogeneous variable resolution ghost imaging method and comprises a laser, a collimation beam expander set, a data processing module, a digital micromirror array device, a coincidence arithmetic unit, a single-point detector, a receiving lens, a receiving light beam, a reflecting mirror, a target, a semi-reflecting and semi-transmitting mirror, a transmitting light beam, non-uniform speckles and a relay lens.
The data processing module comprises a speckle generation sub-module and an image processing sub-module. And the speckle generation submodule is used for operating a speckle generation algorithm to realize speckle generation. And the image processing submodule is used for realizing image processing in the automatic method in the third step, namely, the image processing submodule runs an image processing algorithm, a target is extracted from the image information obtained in the second step by utilizing the type of the interested object which is set in advance, and the circular area where the target object is located is detected. And the coincidence arithmetic unit is applied to the second step and the fourth step to carry out correlation calculation so as to realize image reconstruction.
Loading initial non-uniform annular speckles on the digital micromirror array device according to initialization parameters; light rays are emitted by a laser, pass through the collimation beam expanding lens group, enter the digital micromirror array device to generate a series of non-uniform annular speckle pattern projections, and pass through the semi-reflecting and semi-transparent lens to be projected to a target object. The single-point detector measures the light intensity of the reference light, the light beam reflected by the target object is reflected to the reflector through the semi-reflecting and semi-transparent mirror, the light beam passes through the receiving lens through the reflector and is received by the single-point detector, a measured light intensity signal is obtained, the coincidence arithmetic unit performs correlation calculation on the received speckle light intensity signal and the measured light intensity signal, image reconstruction is achieved, and initial speckle projection, ghost imaging sampling and image reconstruction are completed.
The image processing submodule determines the circle center position of the adaptive speckles and the radius of the high-resolution area by using priori knowledge, and the speckle generation module performs area division, recombination and pixel filling of a random matrix on the classical speckles under a polar coordinate, namely, the heterogeneous speckle with the adaptive adjustment resolution corresponding to the position and the size is generated.
Loading initial non-uniform annular speckles through a digital micro-mirror array device according to initialization parameters, and projecting the initial non-uniform annular speckles onto a target object through a tube laser, wherein the specific implementation method comprises the following steps: after being loaded by the digital micromirror array device, light rays are emitted by the laser, pass through the collimating beam expander set and enter the digital micromirror array device to generate a series of speckle pattern projections. The method for realizing the image reconstruction comprises the following steps of performing correlation calculation on speckle light intensity signals received by a single-point detector and light intensity signals reflected by a corresponding target object to realize the image reconstruction: the single-point detector measures the light intensity of the reference light, the light rays pass through the semi-reflecting and semi-transmitting mirror to be projected to a target object, light beams reflected by the target object are reflected to the reflecting mirror through the semi-reflecting and semi-transmitting mirror, the light beams pass through the receiving lens through the reflecting mirror and are received by the single-point detector, and measured light intensity signals are obtained.
Non-uniform speckles with self-adaptive adjustment resolution corresponding to positions and sizes generated in the loading step of the digital micromirror array device are subjected to three-difference structure; light rays are emitted by a laser, pass through the collimation beam expanding lens group, enter the digital micromirror array device to generate a series of non-uniform annular speckle pattern projections, and pass through the semi-reflecting and semi-transparent lens to be projected to a target object. The single-point detector measures the light intensity of the reference light, the light beam reflected by the target object is reflected to the reflector through the semi-reflecting and semi-transparent mirror, the light beam penetrates through the receiving lens through the reflector and is received by the single-point detector, a measured light intensity signal is obtained, the coincidence arithmetic unit performs correlation calculation on the received speckle light intensity signal and the measured light intensity signal, high-resolution speckle imaging is performed on the sensing area, low-resolution speckle imaging is performed on the non-sensing area, overall graph reconstruction is completed, the data volume is reduced, and therefore ghost imaging efficiency is improved.
Preferably, the invention also discloses a self-adaptive heterogeneous variable resolution ghost imaging method and a system, and the method further comprises a compression sensing module and a deep learning module.
Before the three-step speckle generation submodule operates, the speckle projection quantity is reduced by adding the compressed sensing submodule to reach the Nyquist sampling quantity, the sampling time is reduced, the imaging quality is not damaged, and the imaging efficiency is improved.
And (4) adding a deep learning submodule after the coincidence arithmetic unit in the step four runs, and training the low-resolution image in advance through the deep learning submodule to achieve the purpose of predicting and improving the image after the resolution according to the low-resolution image, so that the high-resolution image reconstruction is realized under the condition of low projection speckle number, the speckle projection number is effectively reduced, and the ghost imaging efficiency is improved.
Has the advantages that:
1. the invention discloses a self-adaptive heterogeneous variable-resolution ghost imaging method and a system, wherein image processing is carried out according to a first ghost imaging result, a circular area where a target object is located is detected through the image processing, non-uniform speckles with adjustable resolution corresponding to the position and the size are generated by determining the position of the circle center of the circular area, the non-uniform speckles are projected to a target for secondary imaging, the generation of the non-uniform speckles is realized by carrying out area division, recombination and pixel filling of a random matrix on classical speckles under polar coordinates, namely, the position of a high-resolution central point is self-adaptively adjusted according to the actual condition requirement, the high-resolution speckle imaging is carried out on an induction area, the low-resolution speckle imaging is carried out on a non-induction area, the data volume is reduced, and the ghost imaging efficiency is further improved.
2. The invention discloses a self-adaptive heterogeneous variable-resolution ghost imaging method and system, which are beneficial to reducing the data volume while realizing high-resolution imaging by realizing non-homogenization on speckles of a digital micromirror array device.
3. According to the self-adaptive heterogeneous variable-resolution ghost imaging method and system, the manual mode can automatically select the region of interest, the automatic mode obtains the region of interest according to the priori knowledge, then the quantization threshold value is set according to the region of interest, and the circle centers of two speckles and the radius size of the high-resolution region which are suitable for different conditions are determined through the automatic method and the manual method.
4. The invention discloses a self-adaptive heterogeneous variable resolution ghost imaging method and system, which merge pixels in a micro-lens array device in a hardware coding mode, have good compatibility, and can be combined with algorithms such as compression sensing, deep learning and the like at the present stage to further improve ghost imaging efficiency, namely: before the three-step speckle generation submodule operates, the speckle projection quantity is reduced by adding the compressed sensing submodule to reach the Nyquist sampling quantity, the sampling time is reduced, the imaging quality is not damaged, and the imaging efficiency is improved. And a deep learning submodule is added after the associated imaging submodule in the step four runs, and the low-resolution image is trained in advance through the deep learning submodule to achieve the purpose of predicting the image after the resolution is improved according to the low-resolution image, so that the high-resolution image reconstruction is realized under the condition of low projection speckle number, the speckle projection number is effectively reduced, and the ghost imaging efficiency is improved.
Drawings
FIG. 1 is a block diagram of an adaptive heterogeneous resolution ghost imaging system in accordance with the present disclosure;
FIG. 2 is a flow chart of a method for adaptive heterogeneous resolution ghost imaging in accordance with the present invention;
FIG. 3 initial resolution non-uniform speckle;
FIG. 4 initial ghost imaging reconstruction;
FIG. 5 modified non-uniform speckle of resolution;
FIG. 6 modified ghost imaging reconstruction.
The system comprises a diode laser 1, a collimating beam expander lens 2, a data processing module 3, a digital micromirror array device 4, a coincidence arithmetic unit 5, a single-point detector 6, a receiving lens 7, a receiving beam 8, a reflecting mirror 9, a target 10, a semi-reflecting and semi-transmitting lens 11, a light emitting beam 12, a non-uniform speckle 13 and a relay lens 14.
Detailed Description
For a better understanding of the objects and advantages of the present invention, reference should be made to the following detailed description taken in conjunction with the accompanying drawings and examples.
Example 1:
as shown in fig. 3, 4, 5, and 6, the present embodiment discloses a self-adaptive heterogeneous resolution ghost imaging method, which includes the following specific steps:
step one, initializing ghost imaging parameter configuration.
Initially configured ghost imaging parameters include high resolution region radius r0, resolution 126 x 126, maximum discrete angle P60, and maximum discrete loop Q40.
And secondly, loading initial non-uniform annular speckles through the digital micro-mirror array device 4 according to the initialization parameters, projecting the initial non-uniform annular speckles onto a target object through the tube diode laser 1, and performing correlation calculation on speckle light intensity signals received by the single-point detector 6 and corresponding light intensity signals reflected by the target 10 object to realize image reconstruction, thereby completing primary speckle projection, ghost imaging sampling and image reconstruction.
The second step is realized by the following concrete method: the number of the projected speckles k, i is 1, 2, k, between the speckle intensity signal Si received by the single-point detector 6 and the corresponding light intensity signal Yi reflected by the object 10.
Ti＝<Si·Yi>-<Si><Yi>
< > represents the statistical mean value, and Ti represents the reconstructed object 10.
And step three, determining the circle center position of the adaptive speckles and the radius of the high-resolution area by using priori knowledge, and performing area division, recombination and pixel filling of a random matrix on the classical speckles under a polar coordinate to generate the self-adaptive resolution adjusting transflective mirror 11 corresponding to the position and the size in an isomeric manner.
The step 3.1 of determining the circle center position of the adaptive speckle and the radius of the high-resolution area comprises an automatic method or a manual method.
The automatic method for determining the circle center position of the adaptive speckle and the radius of the high-resolution area comprises the following steps: and (3) extracting the target 10 from the image information obtained in the step two by using the type of the interested object set in advance through an image processing algorithm, detecting a circular area where the target 10 object is located, determining the position of the circle center of the circular area and the radius of a high-resolution area, improving the resolution to the parameters of the target 10, resetting the maximum value P 'of the discrete angle to be 10, and resetting the maximum value Q' of the discrete ring number to be 40.
The position of the high-resolution center point is adaptively adjusted according to actual situation requirements: it is judged whether or not the resolution of the center area of the target 10 is the resolution of the set high-resolution area. If the resolution is a numerical value set by the high-resolution area, the center position of the area of interest is an initial set circle center coordinate (x0, y 0); if the value is not equal to the value set by the high-resolution area, the central area of the target 10 is reselected as the speckle high-resolution area, and the circle center coordinates are determined (x0, y 0).
Setting the radius of the central area: and obtaining a circumscribed circle of the target 10 object by using an image processing algorithm, determining the maximum distance r0 'between the coordinates of the central point and the outside, and changing r0 into r 0'.
The implementation method for determining the circle center position of the adaptive speckle and the radius of the high-resolution area by a manual method comprises the following steps: the circle center position of the interested region is manually selected, the position of the high-resolution center point is adaptively adjusted according to the actual situation requirement, the circle center coordinates (x0, y0) and the high-resolution region radius r0 ' are set, the maximum value P ' of the discrete angle is reset to be 10, the maximum value Q ' of the discrete ring number is reset to be 40, and the resolution is improved to be the target 10 parameter.
And 3.2, by utilizing the circle center position, the high-resolution area radius, the resolution, the maximum value P 'of the discrete angle and the maximum value Q' of the discrete ring number obtained by an automatic or manual method, generating the transflective mirror 11 by carrying out area division, recombination and pixel filling of a random matrix on the classical speckles under a polar coordinate, namely generating the transflective mirror 11 with self-adaptive resolution adjustment corresponding to the position and the size of heterogeneous generation.
Step four: and projecting the half-reflecting and half-transmitting mirror 11 which is used for adaptively adjusting the resolution and corresponds to the position and the size of the heterogeneous generation in the step III, performing correlation calculation on the obtained reflected light intensity signal and the emitted speckle light intensity, performing high-resolution speckle imaging on the induction area, and performing low-resolution speckle imaging on the non-induction area, thereby completing the reconstruction of the whole graph, reducing the data volume and further improving the ghost imaging efficiency.
The implementation method of the fourth step is as follows: and projecting the half-reflecting and half-transmitting mirror 11 which is used for adaptively adjusting the resolution and corresponds to the position and the size of the heterogeneous generation in the step III, performing correlation calculation on the obtained reflected light intensity signal and the emitted speckle light intensity, performing high-resolution speckle imaging on the induction area, and performing low-resolution speckle imaging on the non-induction area, thereby completing the reconstruction of the whole graph, reducing the data volume and further improving the ghost imaging efficiency.
Before the three-step speckle generation submodule operates, the speckle projection quantity is reduced by adding the compressed sensing submodule to reach the Nyquist sampling quantity, the sampling time is reduced, the imaging quality is not damaged, and the imaging efficiency is improved.
And a deep learning submodule is added after the associated imaging submodule in the step four runs, and the low-resolution image is trained in advance through the deep learning submodule to achieve the purpose of predicting the image after the resolution is improved according to the low-resolution image, so that the high-resolution image reconstruction is realized under the condition of low projection speckle number, the speckle projection number is effectively reduced, and the ghost imaging efficiency is improved.
Example 2:
as shown in fig. 1, this embodiment further discloses a self-adaptive heterogeneous variable resolution ghost imaging system, which is used to implement the self-adaptive heterogeneous variable resolution ghost imaging method, where the system includes a laser 1, a collimating beam expander set 2, a data processing module 3, a digital micromirror array device 4, a coincidence calculator 5, a single-point detector 6, a receiving lens 7, a receiving beam 8, a reflector 9, a target 10, a semi-reflective and semi-transparent mirror 11, a transmitting beam 12, a semi-reflective and semi-transparent mirror 13, and a relay lens 14.
The data processing module 3 includes a speckle generation sub-module, an image processing sub-module, and a coincidence operator 5. And the speckle generation submodule is used for operating a speckle generation algorithm to realize speckle generation. The image processing submodule is used for realizing image processing in the automatic method in the third step, namely, the image processing submodule runs an image processing algorithm, the target 10 is extracted from the image information obtained in the second step by utilizing the type of the interested object which is set in advance, and the circular area where the target 10 is located is detected. The coincidence operator 5 is used for performing correlation calculation in the second and fourth steps to realize image reconstruction.
Loading initial non-uniform annular speckles on the digital micromirror array device 4 according to the initialization parameters; light rays are emitted by a laser 1, pass through a collimation beam expander set 2, enter a digital micro-mirror array device 4, generate a series of non-uniform annular speckle pattern projections, and pass through a semi-reflecting and semi-transparent mirror 11 to be projected to a target object. The single-point detector 6 measures the light intensity of the reference light, the light beam reflected by the target object is reflected to the reflector 9 through the semi-reflecting and semi-transparent mirror 11, the light beam passes through the receiving lens 7 through the reflector 9 and is received by the single-point detector 6, a measured light intensity signal is obtained, the coincidence calculator 5 performs correlation calculation on the received speckle light intensity signal and the measured light intensity signal, image reconstruction is achieved, and initial speckle projection, ghost imaging sampling and image reconstruction are completed.
The image processing submodule determines the circle center position of the self-adaptive speckles and the radius of the high-resolution area by using priori knowledge, and the speckle generating module performs area division, recombination and pixel filling of a random matrix on the classical speckles under a polar coordinate, namely, the image processing submodule generates the self-adaptive resolution adjusting half-reflecting and half-transmitting mirror 11 corresponding to the position and the size in a heterogeneous mode.
Loading initial non-uniform annular speckles through a digital micro-mirror array device 4 according to initialization parameters, and projecting the initial non-uniform annular speckles to a target object through a tube laser 1, wherein the specific implementation method comprises the following steps: after being loaded by the digital micromirror array device 4, light rays are emitted by the laser 1, pass through the collimating beam expander set 2, and enter the digital micromirror array device 4 to generate a series of speckle pattern projections. The speckle light intensity signal received by the single-point detector 6 and the light intensity signal reflected by the corresponding target object are subjected to correlation calculation to realize graph reconstruction, and the specific realization method comprises the following steps: the single-point detector 6 measures the light intensity of the reference light, the light rays pass through the semi-reflecting and semi-transmitting mirror 11 to be projected to a target object, the light beams reflected by the target object are reflected to the reflecting mirror 9 through the semi-reflecting and semi-transmitting mirror 11, the light beams pass through the receiving lens 7 through the reflecting mirror 9 to be received by the single-point detector 6, and measured light intensity signals are obtained.
The digital micromirror array device 4 loads a half-reflecting and half-transmitting mirror 11 which is generated in the three different configurations in the step and corresponds to the position and the size of the self-adaptive adjustment resolution; light rays are emitted by a laser 1, pass through a collimation beam expander set 2, enter a digital micro-mirror array device 4, generate a series of non-uniform annular speckle pattern projections, and pass through a semi-reflecting and semi-transparent mirror 11 to be projected to a target object. The single-point detector 6 measures the light intensity of the reference light, the light beam reflected by the target object is reflected to the reflector 9 through the semi-reflecting and semi-transparent mirror 11, the light beam passes through the receiving lens 7 through the reflector 9 and is received by the single-point detector 6 to obtain a measured light intensity signal, the coincidence calculator 5 performs correlation calculation on the received speckle light intensity signal and the measured light intensity signal, performs high-resolution speckle imaging on the induction area, performs low-resolution speckle imaging on the non-induction area, completes the reconstruction of the whole graph, reduces the data volume and further improves the ghost imaging efficiency.
The adaptive heterogeneous resolution ghost imaging method and system disclosed by the embodiment further comprise a compression sensing module and a deep learning module.
Before the three-step speckle generation submodule operates, the speckle projection quantity is reduced by adding the compressed sensing submodule to reach the Nyquist sampling quantity, the sampling time is reduced, the imaging quality is not damaged, and the imaging efficiency is improved.
And a deep learning submodule is added after the associated imaging submodule in the step four runs, and the low-resolution image is trained in advance through the deep learning submodule to achieve the purpose of predicting the image after the resolution is improved according to the low-resolution image, so that the high-resolution image reconstruction is realized under the condition of low projection speckle number, the speckle projection number is effectively reduced, and the ghost imaging efficiency is improved.
The above detailed description is intended to illustrate the objects, aspects and advantages of the present invention, and it should be understood that the above detailed description is only exemplary of the present invention and is not intended to limit the scope of the present invention, and any modifications, equivalents, improvements and the like made within the spirit and principle of the present invention should be included in the scope of the present invention.
Claims (10)
1. An adaptive heterogeneous variable resolution ghost imaging method, characterized by: comprises the following steps of (a) carrying out,
step one, initializing ghost imaging parameter configuration;
initially configuring ghost imaging parameters including a high resolution region radius r0, a resolution m, a maximum discrete angle P, and a maximum discrete loop number Q;
loading initial non-uniform annular speckles through a digital micro-mirror array device according to the initialization parameters, projecting the initial non-uniform annular speckles onto a target object through a tube laser, and performing correlation calculation on speckle light intensity signals received by a single-point detector and corresponding light intensity signals reflected by the target object to realize image reconstruction so as to complete primary speckle projection, ghost imaging sampling and image reconstruction;
determining the circle center position of the adaptive speckles and the radius of the high-resolution area by using prior knowledge, and performing area division, recombination and pixel filling of a random matrix on the classical speckles under a polar coordinate, namely, generating the non-uniform speckles with adaptive adjustment resolution corresponding to the position and the size in a heterogeneous manner;
step four: and projecting the non-uniform speckles with self-adaptive resolution adjustment corresponding to the positions and sizes of the three heterogeneous generation steps, performing correlation calculation on the obtained reflected light intensity signals and the emitted speckle light intensity, performing high-resolution speckle imaging on the induction area, and performing low-resolution speckle imaging on the non-induction area, thereby completing overall image reconstruction, reducing data volume and further improving ghost imaging efficiency.
2. The adaptive heterogeneous variable resolution ghost imaging method of claim 1, wherein: the second implementation method is that the speckle light intensity signal Si received by the single-point detector and the light intensity signal Yi reflected by the corresponding target object;
Ti＝<Si·Yi>-<Si><Yi>
< > represents the statistical mean value, and Ti represents the reconstructed object.
3. An adaptive heterogeneous resolution ghost imaging method as defined in claim 2, wherein: the realization method of the fourth step is that the heterogeneous generated position and size in the third step are corresponding to the non-uniform speckles with self-adaptive resolution adjustment, correlation calculation is carried out on the obtained reflected light intensity signal and the emitted speckle light intensity, high-resolution speckle imaging is carried out on the sensing area, low-resolution speckle imaging is carried out on the non-sensing area, the whole graph reconstruction is completed, the data volume is reduced, and the ghost imaging efficiency is further improved.
4. An adaptive heterogeneous resolution ghost imaging method according to claim 3, wherein: the third step is to realize the method as follows,
3.1, determining the circle center position of the self-adaptive speckle and the radius of the high-resolution area in an automatic method or a manual method;
and 3.2, utilizing the circle center position, the high-resolution area radius, the resolution, the maximum value P 'of the discrete angle and the maximum value Q' of the discrete ring number obtained by an automatic or manual method, and realizing the generation of the non-uniform speckles by carrying out area division, recombination and pixel filling of a random matrix on the classical speckles under a polar coordinate, namely, the non-uniform speckles with self-adaptive resolution regulation corresponding to the positions and sizes of heterogeneous generation.
5. An adaptive heterogeneous resolution ghost imaging method according to claim 4, wherein: in the step 3.1, the first step of the method,
the automatic method for determining the circle center position of the adaptive speckle and the radius of the high-resolution area comprises the following steps: extracting a target from the image information obtained in the second step by using the type of the interested object set in advance through an image processing algorithm, detecting a circular area where the target object is located, determining the position of the circle center of the circular area and the radius of a high-resolution area, improving the resolution to a target parameter, resetting the maximum value P 'of the discrete angle and the maximum value Q' of the discrete ring number;
the position of the high-resolution center point is adaptively adjusted according to actual situation requirements: judging whether the resolution of the target central area is the resolution of the set high-resolution area or not; if the resolution is a numerical value set by the high-resolution area, the center position of the area of interest is an initial set circle center coordinate (x0, y 0); if the value is not equal to the value set by the high-resolution area, re-selecting the target central area as the speckle high-resolution area, and determining the coordinates of the circle center (x0, y 0);
setting the radius of the central area: obtaining a circumscribed circle of the target object by using an image processing algorithm, determining the maximum distance r0 'between the coordinates of the central point and the outside, and changing r0 into r 0';
the implementation method for determining the circle center position of the adaptive speckle and the radius of the high-resolution area by a manual method comprises the following steps: manually selecting the circle center position of the interested region, adaptively adjusting the position of the high-resolution center point according to the actual condition requirement, setting the circle center coordinates (x0, y0) and the radius r0 ' of the high-resolution region, resetting the maximum value P ' of the discrete angle and the maximum value Q ' of the discrete ring number, and improving the resolution to the target parameter.
6. An adaptive heterogeneous resolution ghost imaging method according to claim 5, wherein: the laser is a diode laser.
7. The adaptive heterogeneous variable resolution ghost imaging method of claim 6, wherein: before the third speckle generation sub-module runs, the compressed sensing sub-module is added to reduce the number of speckle projections to be below the Nyquist sampling number, so that the sampling time is reduced, the imaging quality is not damaged, and the imaging efficiency is improved;
and a deep learning submodule is added after the associated imaging submodule in the step four runs, and the low-resolution image is trained in advance through the deep learning submodule to achieve the purpose of predicting the image after the resolution is improved according to the low-resolution image, so that the high-resolution image reconstruction is realized under the condition of low projection speckle number, the speckle projection number is effectively reduced, and the ghost imaging efficiency is improved.
8. An adaptive heterogeneous resolution ghost imaging system for implementing an adaptive heterogeneous resolution ghost imaging method according to claim 1, 2, 3, 4, 5 or 6, characterized by: the device comprises a laser (1), a collimation beam expander set (2), a data processing module (3), a digital micromirror array device (4), a coincidence arithmetic unit (5), a single-point detector (6), a receiving lens (7), a receiving light beam (8), a reflector (9), a target (10), a semi-reflecting and semi-transmitting lens (11), a transmission light beam (12), non-uniform speckles (13) and a relay lens (14);
the data processing module (3) comprises a speckle generation sub-module, an image processing sub-module and a correlation calculation sub-module; the speckle generation submodule is used for operating a speckle generation algorithm to realize speckle generation; the image processing submodule is used for realizing image processing in the automatic method in the third step, namely, an image processing algorithm is operated through the image processing submodule, a target (10) is extracted from the image information obtained in the second step by utilizing the type of the interested object which is set in advance, and a circular area where the target (10) is located is detected; the correlation calculation submodule is used for performing correlation calculation in the second step and the fourth step to realize image reconstruction;
loading initial non-uniform annular speckles on the digital micromirror array device (4) according to initialization parameters; light rays are emitted by a laser (1), pass through a collimating beam expander lens group (2) and enter a digital micro-mirror array device (4) to generate a series of non-uniform annular speckle pattern projections, and the light rays pass through a semi-reflecting and semi-transparent lens (11) and are projected to an object of a target (10); the single-point detector (6) measures the light intensity of reference light, light beams reflected by an object of a target (10) are reflected to the reflector (9) through the semi-reflecting and semi-transparent mirror (11), the light beams pass through the receiving lens (7) through the reflector (9) and are received by the single-point detector (6), measured light intensity signals are obtained, the correlation calculation submodule performs correlation calculation on the received speckle light intensity signals and the measured light intensity signals, image reconstruction is achieved, and first speckle projection, ghost imaging sampling and image reconstruction are completed;
the image processing submodule determines the circle center position of the self-adaptive speckles and the radius of a high-resolution area by using priori knowledge, and the speckle generation module performs area division, recombination and pixel filling of a random matrix on the classical speckles under a polar coordinate, namely, the heterogeneous speckle (13) with self-adaptive resolution adjustment corresponding to the position and the size is generated;
loading initial non-uniform annular speckles through a digital micro-mirror array device (4) according to initialization parameters, and projecting the initial non-uniform annular speckles onto a target (10) object through a tube laser (1), wherein the specific implementation method comprises the following steps: the light is loaded by a digital micromirror array device (4), and the light is emitted by a laser (1), passes through a collimation beam expanding lens group (2), enters the digital micromirror array device (4) and generates a series of speckle pattern projections; the speckle light intensity signal received by the single-point detector (6) and the light intensity signal reflected by the corresponding object (10) are subjected to correlation calculation to realize graph reconstruction, and the specific realization method comprises the following steps: the single-point detector (6) measures the light intensity of the reference light, the light rays pass through the semi-reflecting and semi-transparent mirror (11) and are projected to a target (10) object, light beams reflected by the target (10) object are reflected to the reflector (9) through the semi-reflecting and semi-transparent mirror (11), the light beams pass through the receiving lens (7) through the reflector (9) and are received by the single-point detector (6), and measured light intensity signals are obtained;
the digital micro-mirror array device (4) loads non-uniform speckles (13) with self-adaptive adjustment resolution corresponding to positions and sizes generated in the step three different types; light rays are emitted by a laser (1), pass through a collimating beam expander lens group (2) and enter a digital micro-mirror array device (4) to generate a series of non-uniform annular speckle pattern projections, and the light rays pass through a semi-reflecting and semi-transparent lens (11) and are projected to an object of a target (10); the single-point detector (6) measures the light intensity of the reference light, the light beam reflected by the object (10) is reflected to the reflector (9) through the semi-reflecting and semi-transparent mirror (11), the light beam passes through the receiving lens (7) through the reflector (9) and is received by the single-point detector (6), a measured light intensity signal is obtained, the correlation calculation submodule performs correlation calculation on the received speckle light intensity signal and the measured light intensity signal, high-resolution speckle imaging is performed on a sensing area, low-resolution speckle imaging is performed on a non-sensing area, overall graph reconstruction is completed, the data volume is reduced, and therefore ghost imaging efficiency is improved.
9. The adaptive heterogeneous variable resolution ghost imaging method of claim 8, wherein: still include the compressed sensing module, before three speckle generation submodule pieces of step operation reduce the speckle through increasing the compressed sensing submodule piece and throw the quantity and reach under the Nyquist sampling quantity under, reduce the sampling time colleague and do not damage imaging quality, promote imaging efficiency.
10. The adaptive heterogeneous variable resolution ghost imaging method of claim 8, wherein: the deep learning sub-module is added after the associated imaging sub-module in the step four runs, and the low-resolution image is trained in advance through the deep learning sub-module to achieve the purpose of predicting the image after the resolution is improved according to the low-resolution image, so that the high-resolution image reconstruction is realized under the condition of low projected speckle number, the speckle projected number is effectively reduced, and the ghost imaging efficiency is improved.
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