Computational ghost imaging system, method and storage medium based on asynchronous differential probing

Abstract

The application provides a kind of computing ghost imaging system, method and storage medium based on asynchronous differential detection, the system includes He-Ne laser, collimating beam expander, spatial light modulator, target object to be imaged, counter, time integration bucket detector, differentiator, counter and computer arranged in sequence.The application introduces asynchronous detection technology into computing ghost imaging system, adjusts and controls the refresh frequency between illumination light source and time integration bucket detector by counter, eliminates the synchronization requirement in computing ghost imaging process, reduces the matching requirement of time integration bucket detector and instrument cost, improves the practicability of computing ghost imaging technology;Differential algorithm is introduced into computing ghost imaging system, differential operation is carried out on the information obtained by time integration bucket detector through differentiator, and the background noise in imaging process can be effectively eliminated, and the image quality of computing ghost imaging is improved.

Description

Technical Field

[0001] This invention relates to the field of optical imaging technology, and in particular to a computational ghost imaging system, method, and storage medium based on asynchronous differential detection. Background Technology

[0002] Computational ghost imaging is a novel lensless imaging technique developed in recent years. It primarily utilizes the intensity fluctuation correlation between two co-originating light fields to acquire image information of unknown target objects. In computational ghost imaging, a collimated and expanded parallel beam is first used to vertically illuminate a programmable spatial light modulator. The light field modulated by the spatial light modulator is then used to illuminate the target object. A bucket detector with no spatial resolution is then used to receive the intensity of the light field modulated by the object. The reference light field in computational ghost imaging can be calculated using the diffraction integral formula. Finally, the intensity distribution of the light field collected by the bucket detector is correlated with that of the reference light field to obtain the image information of the target object. Compared to traditional lens imaging, computational ghost imaging has strong anti-interference capabilities. Because this technique only requires a bucket detector to receive light energy to complete ghost imaging and does not require lens imaging, it can achieve optical imaging of unknown target objects in various complex environments. Due to its unique properties, computational ghost imaging technology has demonstrated great application value in fields such as underwater imaging, remote sensing imaging, medical imaging, astronomical observation, and military reconnaissance, providing an effective new method to solve the imaging problems that traditional imaging technologies struggle to address in complex environments.

[0003] Despite its numerous advantages, computational ghost imaging still faces several limitations in practical applications. For instance, it requires numerous samplings; achieving a single ghost image in a computational ghost imaging experiment necessitates tens of thousands of samples, significantly reducing its imaging efficiency. Furthermore, it demands high synchronization; the barrel detector's detection frequency must strictly match the illumination source's refresh rate, substantially increasing the matching requirements and instrument costs. Finally, the reconstructed image quality is poor, with background noise in the imaging system proving difficult to eliminate, severely hindering its application in high-definition imaging. Recently, researchers proposed an asynchronous detection-based computational ghost imaging technique, which effectively reduces synchronization requirements and instrument costs during imaging, but still increases the number of samplings required to some extent.

[0004] Therefore, it is necessary to propose a computational ghost imaging system and method based on asynchronous differential detection to solve the problems of low imaging efficiency, high synchronization requirements and poor image quality in existing computational ghost imaging techniques. Summary of the Invention

[0005] To address these issues, embodiments of the present invention propose a computational ghost imaging system, method, and storage medium based on asynchronous differential detection, which solves the aforementioned technical problems.

[0006] This invention proposes a computational ghost imaging system based on asynchronous differential detection, wherein the system comprises the following components arranged sequentially along the optical path:

[0007] The system comprises a He-Ne laser, a collimating beam expander, a spatial light modulator, a target object to be imaged, a time-integrating barrel detector, a differential converter, a counter, and a computer, wherein the target object to be imaged is placed between the spatial light modulator and the counter.

[0008] The spatial light modulator is connected to the time-integrating bucket detector via the counter, the spatial light modulator is connected to the differential via the computer, and the time-integrating bucket detector is connected to the computer via the differential. The computer is used to acquire image information of the target object to be imaged through computational ghost imaging technology based on asynchronous differential detection.

[0009] This invention also proposes a computational ghost imaging method based on asynchronous differential detection, which is implemented using the computational ghost imaging system based on asynchronous differential detection as described above. The method includes the following steps:

[0010] Step 1: Collimate and expand the He-Ne laser beam using collimating and beam-expanding lenses to produce a uniformly distributed parallel beam.

[0011] By controlling the support of the He-Ne laser and adjusting the emission direction of the He-Ne laser beam with a knob, the He-Ne laser beam is kept horizontally emitted. Then, the collimating and expanding mirrors are used to collimate and expand the He-Ne laser beam to produce a uniformly distributed parallel beam.

[0012] Step 2: Modulate the parallel beam using a spatial light modulator to generate a random speckle light field:

[0013] M random speckle patterns of size P×Q are generated using computer software. The size of the random speckle pattern is set to be the same as the effective modulation size of the spatial light modulator to ensure that each pixel in the random speckle pattern can be effectively modulated. P×Q represents the pixel size of the random speckle pattern loaded by the spatial light modulator, P represents the pixel width of the random speckle pattern, and Q represents the pixel height of the random speckle pattern.

[0014] A parallel beam of light is incident perpendicularly onto the liquid crystal panel of the spatial light modulator. Then, computer software is used to sequentially load M random speckle patterns onto the spatial light modulator at a first preset frequency F0 to generate a series of random speckle light fields. m represents the number of times the spatial light modulator is loaded, p∈[1,P], q∈[1,Q];

[0015] Step 3: Utilize a time-integrating bucket detector to receive the light energy information of the target object after it has been illuminated by a random speckle light field.

[0016] The target object T(p, q) is illuminated perpendicularly by a random speckle light field modulated by a spatial light modulator;

[0017] Then, a time-integrating bucket detector is used to receive the light energy information C modulated by the target object to be imaged at a preset detection frequency F1. (n) ;

[0018] Step 4: Use a differential converter to perform differential operations on the light energy information to obtain differential information:

[0019] The optical energy information received by the time-integrating bucket detector is differentially processed using a differential converter. When no random speckle pattern is loaded onto the spatial light modulator, the optical field intensity after the spatial light modulator is denoted as... The light energy information received by the time-integrating bucket detector is denoted as C. (0) The difference information of the nth iteration is denoted as:

[0020] D (n) =C (n) -C (n-1) where n = 1, 2, ... N

[0021] Among them, D (n) This represents the differential information obtained by the differential converter from the information detected by the time-integrating bucket detector in the nth time, where N represents the maximum number of detections by the time-integrating bucket detector.

[0022] The intensity distribution of the reference light field during the m-th loading in the ghost imaging process was calculated using the diffraction integral formula.

[0023] Step 5: Obtain the ghost image of the target object through differential correlation operation:

[0024] Ghost imaging images are obtained by correlating the reference light field intensity distribution with the differential information.

[0025] The computational ghost imaging method based on asynchronous differential detection, wherein in step two, the number of random speckle patterns loaded, M, is 600, the first preset frequency F0 corresponding to the loading is 1 / 60Hz, the pixel size P×Q of the random speckle pattern is 200×200, and the pixel size of each unit of the spatial light modulator is 12μm×12μm.

[0026] The computational ghost imaging method based on asynchronous differential detection, wherein in step three, the ratio of the first preset frequency F0 of the random speckle pattern loaded by the spatial light modulator to the preset detection frequency F1 of the time-integrating bucket detector is defined as the asynchronous multiplier K, and the formula for calculating the asynchronous multiplier K is expressed as follows:

[0027] K = F0 / F1

[0028] When the number of amplitudes of the random speckle pattern loaded by the spatial light modulator is M, the maximum number of detections N of the time-integrating bucket detector is expressed as:

[0029] N = M / K

[0030] Where K takes a value greater than or equal to 2.

[0031] The computational ghost imaging method based on asynchronous differential detection is described in which the preset detection frequency F1 of the time integration bucket detector is 1 / 20Hz, the asynchronous multiplier K is 3, and the maximum number of detections N of the time integration bucket detector is 200.

[0032] The computational ghost imaging method based on asynchronous differential detection, wherein in step four, the intensity distribution of the reference light field during the m-th loading in the ghost imaging process is calculated using the diffraction integral formula. In the steps, the reference light field intensity distribution The calculation formula is expressed as:

[0033]

[0034] in, Represents a random speckle light field. denoted as convolution operator, λ as wavelength of incident light, z as distance between the rear surface of the spatial light modulator and the front surface of the target object, p(x, y) as pupil function of the spatial light modulator, x as x-coordinate of the plane of the spatial light modulator, y as y-coordinate of the plane of the spatial light modulator, and j as complex number.

[0035] In the computational ghost imaging method based on asynchronous differential detection, the expression for the pupil function p(x, y) of the spatial light modulator is:

[0036]

[0037] Where x0 = y0 = 2400um.

[0038] The computational ghost imaging method based on asynchronous differential detection, wherein in step five, the method for obtaining a ghost imaging image by correlating the reference light field intensity distribution with the differential information, is expressed by the following formula:

[0039]

[0040] Where G(p, q) represents the ghost image.

[0041] The present invention also proposes a storage medium, wherein a computer program is stored on the storage medium, and when the computer program is executed by a processor, it implements the computational ghost imaging method based on asynchronous differential detection as described in any of the above.

[0042] The present invention has the following beneficial effects:

[0043] 1. This invention introduces asynchronous detection technology into the computational ghost imaging system. By using a counter to adjust and control the refresh frequency between the illumination source and the time integration barrel detector, the synchronization requirements in the computational ghost imaging process are eliminated, the matching requirements of the time integration barrel detector and the instrument cost are reduced, and the practicality of computational ghost imaging technology is improved.

[0044] 2. This invention introduces a differential algorithm into the computational ghost imaging system. By performing differential operations on the information obtained by the time-integrating bucket detector through a differential converter, the background noise during the imaging process can be effectively eliminated, and the image quality of computational ghost imaging can be improved.

[0045] 3. This invention combines the differential algorithm with asynchronous detection technology and applies it to correlation operations, eliminating speckle noise caused by asynchronous detection and significantly reducing the number of samplings required for computational ghost imaging technology, thereby improving the imaging efficiency of the computational ghost imaging system.

[0046] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by means of embodiments of the invention. Attached Figure Description

[0047] The above and / or additional aspects and advantages of the embodiments of the present invention will become apparent and readily understood from the description of the embodiments in conjunction with the following drawings, wherein:

[0048] Figure 1 This is a schematic diagram of the computational ghost imaging system based on asynchronous differential detection proposed in this invention. Detailed Implementation

[0049] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0050] Please see Figure 1 The present invention proposes a computational ghost imaging system based on asynchronous differential detection, wherein the system includes a He-Ne laser 101, a collimating beam expander 102, a spatial light modulator 103, a target object 104 to be imaged, a time-integrating bucket detector 105, a differential 106, a counter 107, and a computer 108 arranged sequentially on the optical path, wherein the target object 104 to be imaged is placed between the spatial light modulator and the counter.

[0051] In this embodiment, the spatial light modulator 103 and the time-integrating bucket detector 105 are connected via a counter 107, and the spatial light modulator 103 and the differential detector 106 are connected via a computer 108. The time-integrating bucket detector 105 and the computer 108 are connected via the differential detector 106, and the computer 108 is used to acquire image information of the target object to be imaged through computational ghost imaging technology based on asynchronous differential detection.

[0052] This invention also proposes a computational ghost imaging method based on asynchronous differential detection, which is implemented using the computational ghost imaging system based on asynchronous differential detection as described above. The method includes the following steps:

[0053] Step 1: Collimate and expand the He-Ne laser beam using a collimating and expanding lens to produce a uniformly distributed parallel beam.

[0054] Specifically, in step one, by controlling the support of the He-Ne laser, the emission direction of the He-Ne laser beam is adjusted by the knob to keep the He-Ne laser beam emitted horizontally. Then, the collimating and expanding mirrors are used to collimate and expand the He-Ne laser beam to produce a uniformly distributed parallel beam.

[0055] Step 2: Modulate the parallel beam using a spatial light modulator to generate a random speckle light field.

[0056] In this invention, step two specifically includes steps 2.1 and 2.2, as described below:

[0057] Step 2.1: Use computer software to generate M random speckle patterns of size P×Q; wherein, the size of the random speckle pattern is set to be the same as the effective modulation size of the spatial light modulator to ensure that each pixel in the random speckle pattern can be effectively modulated; P×Q represents the pixel size of the random speckle pattern loaded by the spatial light modulator, P represents the pixel width of the random speckle pattern, and Q represents the pixel height of the random speckle pattern.

[0058] Step 2.2: A parallel beam of light is incident perpendicularly onto the liquid crystal panel of the spatial light modulator. Then, computer software is used to sequentially load M random speckle patterns onto the spatial light modulator at a first preset frequency F0 to generate a series of random speckle light fields. m represents the number of times the spatial light modulator is loaded, p∈[1,P], q∈[1,Q].

[0059] In this embodiment, the number of random speckle patterns loaded, M, is 600, the first preset frequency F0 corresponding to the loading is 1 / 60Hz, the pixel size P×Q of the random speckle pattern is 200×200, and the pixel size of each unit of the spatial light modulator is 12μm×12μm.

[0060] Step 3: Use a time-integrating bucket detector to receive the light energy information of the target object after it has been illuminated by a random speckle light field.

[0061] In this invention, step three specifically includes steps 3.1 and 3.2, as described below:

[0062] Step 3.1: Illuminate the target object T(p, q) perpendicularly with a random speckle light field modulated by a spatial light modulator;

[0063] Step 3.2: Then, using a time-integrating bucket detector, the light energy information C modulated by the target object to be imaged is received at a preset detection frequency F1. (n) .

[0064] In this embodiment, the ratio of the first preset frequency F0 of the random speckle pattern loaded by the spatial light modulator to the preset detection frequency F1 of the time-integrating bucket detector is defined as the asynchronous multiplier K, and the formula for calculating the asynchronous multiplier K is expressed as follows:

[0065] K = F0 / F1

[0066] When the number of amplitudes of the random speckle pattern loaded by the spatial light modulator is M, the maximum number of detections N of the time-integrating bucket detector is expressed as:

[0067] N = M / K

[0068] Where K takes a value greater than or equal to 2.

[0069] Asynchronous detection can significantly reduce the amount of detection data, lowering the detection requirements and information storage of computational ghost imaging technology. In practical applications, the preset detection frequency F1 of the time-integrating bucket detector is set to 1 / 20Hz, the asynchronous multiplier K is set to 3, and the maximum number of detections N is 200.

[0070] Step 4: Use a differential converter to perform differential operations on the light energy information to obtain differential information.

[0071] In this invention, step four specifically includes steps 4.1 and 4.2, as described below:

[0072] Step 4.1: Perform differential calculations on the optical energy information received by the time-integrating bucket detector using a differential converter. When no random speckle pattern is loaded onto the spatial light modulator, the optical field intensity after the spatial light modulator is denoted as... The light energy information received by the time-integrating bucket detector is denoted as C. (0) The difference information of the nth iteration is denoted as:

[0073] D (n) =C (n) -C (n-1) where n = 1, 2, ... N

[0074] Among them, D (n) This represents the differential information obtained by the differential converter from the information detected by the time-integrating bucket detector in the nth time, where N represents the maximum number of detections by the time-integrating bucket detector.

[0075] Step 4.2: Calculate the intensity distribution of the reference light field during the m-th loading in the ghost imaging process using the diffraction integral formula.

[0076] Specifically, the reference light field intensity distribution The calculation formula is expressed as:

[0077]

[0078] in, Represents a random speckle light field. denoted as convolution operator, λ as wavelength of incident light, z as distance between the rear surface of the spatial light modulator and the front surface of the target object, p(x, y) as pupil function of the spatial light modulator, x as x-coordinate of the plane of the spatial light modulator, y as y-coordinate of the plane of the spatial light modulator, and j as complex number.

[0079] Furthermore, the expression for the pupil function p(x, y) of the spatial light modulator is:

[0080]

[0081] Where x0 = y0 = 2400um.

[0082] Step 5: Obtain the ghost image of the target object through differential correlation operation.

[0083] In this step, a ghost imaging image is obtained by performing correlation calculations based on the reference light field intensity distribution and differential information.

[0084] In this step, the method for obtaining a ghost image by correlating the reference light field intensity distribution with differential information is expressed by the following formula:

[0085]

[0086] Where G(p, q) represents the ghost image.

[0087] The differential correlation operation in the above formula not only obtains the computational ghost image of the target, but also eliminates speckle noise caused by asynchronous detection technology, significantly reducing the number of samplings required for imaging. This improves both the image quality of the computational ghost image and the imaging efficiency. This technology is feasible both in principle and experimentally, and has already been verified in the laboratory.

[0088] The present invention also proposes a storage medium, wherein a computer program is stored on the storage medium, and when the computer program is executed by a processor, it implements the computational ghost imaging method based on asynchronous differential detection as described in any of the above.

[0089] The present invention has the following beneficial effects:

[0090] 1. This invention introduces asynchronous detection technology into the computational ghost imaging system. By using a counter to adjust and control the refresh frequency between the illumination source and the time integration barrel detector, the synchronization requirements in the computational ghost imaging process are eliminated, the matching requirements of the time integration barrel detector and the instrument cost are reduced, and the practicality of computational ghost imaging technology is improved.

[0091] 2. This invention introduces a differential algorithm into the computational ghost imaging system. By performing differential operations on the information obtained by the time-integrating bucket detector through a differential converter, the background noise during the imaging process can be effectively eliminated, and the image quality of computational ghost imaging can be improved.

[0092] 3. This invention combines the differential algorithm with asynchronous detection technology and applies it to correlation operations, eliminating speckle noise caused by asynchronous detection and significantly reducing the number of samplings required for computational ghost imaging technology, thereby improving the imaging efficiency of the computational ghost imaging system.

[0093] It should be understood that various parts of the present invention can be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, it can be implemented using any one or a combination of the following techniques known in the art: discrete logic circuits having logic gates for implementing logical functions on data signals, application-specific integrated circuits (ASICs) having suitable combinational logic gates, programmable gate arrays (PGAs), field-programmable gate arrays (FPGAs), etc.

[0094] In the description of this specification, references to terms such as "one embodiment," "some embodiments," "example," "specific example," or "some examples," etc., indicate that a specific feature, structure, material, or characteristic described in connection with that embodiment or example is included in at least one embodiment or example of the invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0095] Although embodiments of the invention have been shown and described, those skilled in the art will understand that various changes, modifications, substitutions and alterations can be made to these embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.

Claims

1. A computational ghost imaging method based on asynchronous differential detection, characterized in that, The method includes the following steps: Step 1: Collimate and expand the He-Ne laser beam using collimating and beam-expanding lenses to produce a uniformly distributed parallel beam. By controlling the support of the He-Ne laser and adjusting the emission direction of the He-Ne laser beam with a knob, the He-Ne laser beam is kept horizontally emitted. Then, the collimating and expanding mirrors are used to collimate and expand the He-Ne laser beam to produce a uniformly distributed parallel beam. Step 2: Modulate the parallel beam using a spatial light modulator to generate a random speckle light field: Generate using computer software M The size is P×Q The random speckle pattern; wherein the size of the random speckle pattern is set to be the same as the effective modulation size of the spatial light modulator, so as to ensure that each pixel in the random speckle pattern can be effectively modulated. P×Q This represents the pixel size of the random speckle pattern loaded by the spatial light modulator. P This represents the pixel width of the random speckle pattern. Q Represents the pixel height of the random speckle pattern; A parallel beam of light is incident perpendicularly onto the LCD panel of the spatial light modulator, and then computer software is used to... M A random speckle pattern is generated according to a first preset frequency. F 0 is sequentially loaded onto the spatial light modulator to generate a series of random speckle light fields. , m Indicates the number of times the spatial light modulator is loaded. , ; Step 3: Utilize a time-integrating bucket detector to receive the light energy information of the target object after it has been illuminated by a random speckle light field. The target object is illuminated perpendicularly by a random speckle light field modulated by a spatial light modulator. ; Then, a time-integrating bucket detector is used at a preset detection frequency. F 1. Receive light energy information modulated by the target object to be imaged. ; Step 4: Use a differential converter to perform differential operations on the light energy information to obtain differential information: The optical energy information received by the time-integrating bucket detector is differentially processed using a differential converter. When no random speckle pattern is loaded onto the spatial light modulator, the optical field intensity after the spatial light modulator is denoted as... The light energy information received by the time-integrating bucket detector is denoted as... Then the first n The difference information of each step is denoted as: ； in, This indicates the differential converter for the time integrating bucket detector. n Differential information is obtained by differentiating the information detected in the second step. N Indicates the maximum number of detections by the time integration bucket detector; The first step in the ghost imaging process is calculated using the diffraction integral formula. m Reference light field intensity distribution after secondary loading ; Step 5: Obtain the ghost image of the target object through differential correlation operation: Ghost imaging images are obtained by correlating the reference light field intensity distribution with the differential information.

2. The computational ghost imaging method based on asynchronous differential detection according to claim 1, characterized in that, In step two, the number of random speckle patterns loaded M The number of images is 600, and the corresponding first preset frequency during loading is... F 0 represents 1 / 60Hz, the pixel size of the random speckle pattern. P×Q The value is 200 × 200, the size of each unit pixel in the spatial light modulator is .

3. The computational ghost imaging method based on asynchronous differential detection according to claim 2, characterized in that, In step three, the first preset frequency of the random speckle pattern loaded by the spatial light modulator is... F 0 and the preset detection frequency of the time integration bucket detector F The ratio of 1 is defined as the asynchronous multiplier. K Asynchronous multiplier K The calculation formula is expressed as: ； When the spatial light modulator loads a random speckle pattern with an amplitude of 1000,000, M At that time, the maximum number of detections by the time integration bucket detector N Represented as: ； in, K The value of is greater than or equal to 2.

4. The computational ghost imaging method based on asynchronous differential detection according to claim 3, characterized in that, Preset detection frequency of the time integration bucket detector F The value of 1 is 1 / 20Hz, which is the asynchronous frequency. K The value is 3, which represents the maximum number of detections by the time integration bucket detector. N It is 200 times.

5. The computational ghost imaging method based on asynchronous differential detection according to claim 4, characterized in that, In step four, the first step in the ghost imaging process is calculated using the diffraction integral formula. m Reference light field intensity distribution after secondary loading In the steps, the reference light field intensity distribution The calculation formula is expressed as: ； in, Represents a random speckle light field. This represents the convolution operator. Indicates the wavelength of the incident light. This represents the distance between the rear surface of the spatial light modulator and the front surface of the target object to be imaged. The pupil function represents the spatial light modulator. This represents the x-coordinate of the spatial light modulator plane. Represents the ordinate of the spatial light modulator plane. It represents a complex number.

6. The computational ghost imaging method based on asynchronous differential detection according to claim 5, characterized in that, Pupil function of spatial light modulator The expression is: ； in, .

7. The computational ghost imaging method based on asynchronous differential detection according to claim 6, characterized in that, In step five, the method for obtaining a ghost image by correlation calculation based on the reference light field intensity distribution and differential information is expressed by the following formula: in, This represents a ghost image.

8. A computational ghost imaging system based on asynchronous differential detection, said system being applied to the computational ghost imaging method based on asynchronous differential detection according to any one of claims 1-7, characterized in that, The system comprises the following components arranged sequentially along the optical path: The system comprises a He-Ne laser, a collimating beam expander, a spatial light modulator, a target object to be imaged, a time-integrating barrel detector, a differential converter, a counter, and a computer, wherein the target object to be imaged is placed between the spatial light modulator and the counter. The spatial light modulator is connected to the time-integrating bucket detector via the counter, the spatial light modulator is connected to the differential via the computer, and the time-integrating bucket detector is connected to the computer via the differential. The computer is used to acquire image information of the target object to be imaged through computational ghost imaging technology based on asynchronous differential detection.

9. A storage medium, characterized in that, The storage medium stores a computer program, which, when executed by a processor, implements the computational ghost imaging method based on asynchronous differential detection as described in any one of claims 1-7.

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