Dynamic computational imaging methods

Abstract

The present invention discloses a dynamic computational imaging method, which belongs to the technical field of data processing. The present invention obtains imaging sensor data and dynamic sensor data, wherein the dynamic sensor data is the frame data of the next time period of the imaging sensor data; generates a preliminary imaging image according to the imaging sensor data; and optimizes the preliminary imaging image according to the dynamic sensor data to obtain a dynamic imaging image. In this way, it is achieved that frame data at two moments are collected during imaging, and then the image imaged by the current cycle data is optimized based on the frame data of the next cycle, thereby achieving dynamic imaging and improving image quality.

Description

Technical Field

[0001] The present invention relates to the technical field of data processing, and in particular to a dynamic computational imaging method. Background Art

[0002] Currently, imaging of sensor data mostly involves directly collecting sensor data and then performing direct imaging based on the sensor data. However, this method only relies on a set of data at a single moment for imaging. If only one image is referenced, if the object is moving, the final image will be blurred or the imaging effect will be poor.

[0003] The above contents are only used to assist in understanding the technical solution of the present invention and do not constitute an admission that the above contents are prior art. Summary of the invention

[0004] The main purpose of the present invention is to provide a dynamic computational imaging method, aiming to solve the technical problem that the imaging in the prior art is prone to blur or poor effect.

[0005] To achieve the above object, the present invention provides a dynamic computational imaging method, which comprises the following steps:

[0006] Acquire imaging sensor data and dynamic sensor data, wherein the dynamic sensor data is frame data of the imaging sensor data in the next time period;

[0007] generating a preliminary imaging image based on the imaging sensor data;

[0008] The preliminary imaging image is optimized according to the dynamic sensor data to obtain a dynamic imaging image.

[0009] Optionally, acquiring imaging sensor data and dynamic sensor data includes:

[0010] Collect sensor data;

[0011] Splitting the sensor data into multiple groups of frame data according to a preset cycle duration;

[0012] Imaging sensor data and dynamic sensor data are extracted from each set of frame data according to the current cycle.

[0013] Optionally, generating a preliminary imaging image according to the imaging sensor data comprises:

[0014] Obtaining image point data according to the imaging sensor data;

[0015] Determine imaging point position information and imaging point color information according to the image point data;

[0016] A preliminary imaging image is generated according to the imaging point position information and the imaging point color information.

[0017] Optionally, optimizing the preliminary imaging image according to the dynamic sensor data to obtain a dynamic imaging image includes:

[0018] Determining fitting image data according to the dynamic sensor data;

[0019] The fitting image data is compared with the preliminary imaging image, and the preliminary imaging image is optimized according to the comparison result to obtain a dynamic imaging image.

[0020] Optionally, comparing the fitting image data with the preliminary imaging image, and optimizing the preliminary imaging image according to the comparison result to obtain a dynamic imaging image, comprises:

[0021] Determining image point dynamic information according to the fitted image data;

[0022] Comparing the image point dynamic information with the preliminary imaging image;

[0023] Obtaining the changed image point information according to the comparison result;

[0024] The preliminary imaging image is optimized according to the changed image point information to obtain a dynamic imaging image.

[0025] Optionally, optimizing the preliminary imaging image according to the changed image point information to obtain a dynamic imaging image includes:

[0026] Determining change semantic information according to the change image point information;

[0027] Determining an adjustment strategy for the preliminary image according to the change semantic information;

[0028] The image points in the preliminary imaging image are adjusted by the adjustment strategy to obtain a dynamic imaging image.

[0029] Optionally, determining an adjustment strategy for the preliminary image according to the change semantic information includes:

[0030] determining an imaging change scene according to the change semantic information;

[0031] Determining an imaging modification strategy according to the imaging change scenario;

[0032] Determining an adjustment strategy for the preliminary imaging image according to the imaging modification strategy

[0033] In addition, to achieve the above-mentioned purpose, the present invention further proposes a dynamic computational imaging device, the dynamic computational imaging device comprising:

[0034] A data acquisition module, used to acquire imaging sensor data and dynamic sensor data, wherein the dynamic sensor data is frame data of the imaging sensor data in the next time period;

[0035] A preliminary generation module, used to generate a preliminary imaging image according to the imaging sensor data;

[0036] The dynamic imaging module is used to optimize the preliminary imaging image according to the dynamic sensor data to obtain a dynamic imaging image.

[0037] In addition, to achieve the above objective, the present invention further proposes a computer device, which includes: a memory and a processor, and when the processor runs the computer instructions stored in the memory, the processor executes the method described above.

[0038] In addition, to achieve the above objective, the present invention further proposes a medium, comprising instructions, which, when executed on a computer device, enable the computer device to execute the method described above.

[0039] The present invention obtains imaging sensor data and dynamic sensor data, wherein the dynamic sensor data is the frame data of the next time period of the imaging sensor data; generates a preliminary imaging image according to the imaging sensor data; and optimizes the preliminary imaging image according to the dynamic sensor data to obtain a dynamic imaging image. In this way, it is achieved that frame data at two moments are collected during imaging, and then the image imaged by the current cycle data is optimized based on the frame data of the next cycle, thereby achieving dynamic imaging and improving image quality. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 It is a structural diagram of a dynamic computing imaging device in a hardware operating environment involved in an embodiment of the present invention;

[0041] Figure 2 It is a schematic diagram of the flow chart of the first embodiment of the dynamic computational imaging method of the present invention;

[0042] Figure 3 It is a schematic diagram of the flow chart of the second embodiment of the dynamic computational imaging method of the present invention;

[0043] Figure 4 It is a structural block diagram of the first embodiment of the dynamic computing imaging device of the present invention.

[0044] The realization of the purpose, functional features and advantages of the present invention will be further explained in conjunction with embodiments and with reference to the accompanying drawings. DETAILED DESCRIPTION

[0045] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below through the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0046] Reference Figure 1 , Figure 1 A schematic diagram of the computer device structure of the hardware operating environment involved in the embodiment of the present invention.

[0047] like Figure 1 As shown, the computer device may include: a processor 1001, such as a central processing unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Among them, the communication bus 1002 is used to realize the connection and communication between these components. The user interface 1003 may include a display screen (Display), an input unit such as a keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface and a wireless interface. The network interface 1004 may optionally include a standard wired interface and a wireless interface (such as a wireless fidelity (Wireless-Fidelity, Wi-Fi) interface). The memory 1005 may be a high-speed random access memory (Random Access Memory, RAM), or a stable non-volatile memory (Non-Volatile Memory, NVM), such as a disk storage. The memory 1005 may also be a storage device independent of the aforementioned processor 1001.

[0048] Those skilled in the art will understand that Figure 1 The structure shown in the figure does not constitute a limitation on the computer device, and may include more or less components than shown in the figure, or combine some components, or arrange the components differently.

[0049] like Figure 1 As shown, the memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a dynamic computational imaging program.

[0050] exist Figure 1 In the computer device shown, the network interface 1004 is mainly used for data communication with the network server; the user interface 1003 is mainly used for data interaction with the user; the processor 1001 and the memory 1005 in the computer device of the present invention can be set in the computer device, and the computer device calls the dynamic computational imaging program stored in the memory 1005 through the processor 1001, and executes the dynamic computational imaging method provided by the embodiment of the present invention.

[0051] The embodiment of the present invention provides a dynamic computational imaging method, referring to Figure 2 , Figure 2 FIG. 4 is a flow chart of a first embodiment of a dynamic computational imaging method according to the present invention.

[0052] In this embodiment, the dynamic computational imaging method includes the following steps:

[0053] Step S10: acquiring imaging sensor data and dynamic sensor data, wherein the dynamic sensor data is frame data of the imaging sensor data in the next time period.

[0054] It should be noted that in the solution of this embodiment, the execution subject can be any intelligent terminal, such as a computer, a laptop, a server or a smart phone, or other intelligent devices with information processing functions, which is not limited in this embodiment.

[0055] It should be noted that both the imaging sensor data and the dynamic sensor data are collected through pre-set sensors. Specifically, the sensor may be an image acquisition device such as a camera or a monitor.

[0056] At present, the imaging of sensor data is mostly done by directly collecting sensor data and then performing direct imaging based on the sensor data. However, this method only relies on a set of data at a single moment for imaging. If only one image is referenced, if the object is moving, the final image will be blurred or the imaging effect will be poor. The solution of this embodiment is to obtain imaging sensor data and dynamic sensor data, wherein the dynamic sensor data is the frame data of the next time period of the imaging sensor data; generate a preliminary imaging image based on the imaging sensor data; and optimize the preliminary imaging image based on the dynamic sensor data to obtain a dynamic imaging image. In this way, it is possible to collect frame data at two moments during imaging, and then optimize the image imaged by the current cycle data based on the frame data of the next cycle, thereby achieving dynamic imaging and improving image quality.

[0057] It should be understood that the imaging sensor data refers to the sensor data that determines the moment when imaging is required, and the dynamic sensor data is the frame data of the next time period of the imaging sensor data, that is, the data collected at the moment after the next period after the dynamic sensor data is collected. The specific length of the time period can be set in advance, and this embodiment does not limit this.

[0058] Furthermore, in order to accurately collect imaging sensor data and dynamic sensor data, step S10 includes: collecting sensor data; splitting the sensor data into multiple groups of frame data according to a preset cycle duration; and extracting imaging sensor data and dynamic sensor data from each group of frame data according to the current cycle.

[0059] In a specific implementation, the preset sensor data is first collected, and then the sensor data is split into multiple groups of frame data according to the preset cycle duration, so that a group of frame data corresponding to the imaging moment can be determined as imaging sensor data according to the imaging moment, and then the frame data corresponding to the next cycle duration of the imaging moment is used as dynamic sensor data. The imaging moment is the imaging moment operated by the user, such as: the screenshot moment, the preset moment, or the moment when the camera presses the shutter, etc.

[0060] Step S20: generating a preliminary imaging image according to the imaging sensor data.

[0061] It should be noted that after the two groups of data, the imaging sensor data and the dynamic sensor data, are determined, a preliminary image is firstly generated based on the imaging sensor data.

[0062] Furthermore, in order to generate a preliminary imaging image, step S20 includes: obtaining image point data according to the imaging sensor data; determining imaging point position information and imaging point color information according to the image point data; and generating a preliminary imaging image according to the imaging point position information and the imaging point color information.

[0063] It should be understood that the image point data is first determined based on the imaging sensor data, that is, the data corresponding to each image point contained in the imaging sensor data. The image point may also be a pixel point. Then, the imaging point position and the imaging point color are determined based on the image point data, that is, the coordinates of the position of each image point and the corresponding color information, so that a preliminary imaging image can be generated on a drawing or canvas.

[0064] Step S30: Optimizing the preliminary imaging image according to the dynamic sensor data to obtain a dynamic imaging image.

[0065] In the specific implementation,

[0066] This embodiment acquires imaging sensor data and dynamic sensor data, wherein the dynamic sensor data is the frame data of the next time period of the imaging sensor data; generates a preliminary imaging image according to the imaging sensor data; and optimizes the preliminary imaging image according to the dynamic sensor data to obtain a dynamic imaging image. In this way, it is achieved that frame data at two moments are collected during imaging, and then the image imaged by the current cycle data is optimized based on the frame data of the next cycle, thereby achieving dynamic imaging and improving image quality.

[0067] refer to Figure 3 , Figure 3 FIG. 4 is a flow chart of a second embodiment of a dynamic computational imaging method according to the present invention.

[0068] Based on the first embodiment, the dynamic computational imaging method of this embodiment includes in step S30:

[0069] Step S301: determining fitting image data according to the dynamic sensor data.

[0070] It should be noted that first, the fitting image data is determined based on the dynamic sensor data. The specific means can be to perform pseudo-generation of the image through the dynamic sensor data to determine the data of the corresponding image points, or to directly classify and summarize the dynamic sensor data according to the positions of the image points to obtain the fitting image data.

[0071] Step S302: comparing the fitting image data with the preliminary imaging image, and optimizing the preliminary imaging image according to the comparison result to obtain a dynamic imaging image.

[0072] It should be understood that after obtaining the fitted image data, the data of each image point in the fitted image data is compared with the preliminary imaging image to determine whether there are changes and deviations in the data and information corresponding to the same image point. The preliminary imaging image can be optimized and modified based on whether there are changes and deviations in the data and information corresponding to the same image point in the comparison results to obtain a dynamic imaging image.

[0073] Furthermore, in order to perform image optimization, step S302 includes: determining image point dynamic information based on the fitted image data; comparing the image point dynamic information with the preliminary imaging image; obtaining changed image point information based on the comparison result; optimizing the preliminary imaging image based on the changed image point information to obtain a dynamic imaging image.

[0074] In the specific implementation, the dynamic information of the image points is first determined based on the fitted image data, that is, the image points with color changes in the fitted image data and the preliminary imaging image are determined, and then a comparison is performed to determine the specific changed color or contrast data as the comparison result.

[0075] It should be noted that after obtaining the comparison results, the changed image point information is determined based on the comparison results. The changed image point information refers to the summary information of image points at the same position where color, contrast, or saturation changes occur. After obtaining the changed image point information, the semantics of the change is determined based on the changed image point information, so that the preliminary imaging image can be adjusted and optimized in a targeted manner to obtain the final dynamic imaging image.

[0076] Furthermore, in order to optimize through the relevant information of the changing image points, the preliminary imaging image is optimized according to the changing image point information, and the step of obtaining the dynamic imaging image includes: determining the changing semantic information according to the changing image point information; determining the adjustment strategy of the preliminary imaging image according to the changing semantic information; adjusting the image points in the preliminary imaging image according to the adjustment strategy to obtain the dynamic imaging image.

[0077] It should be understood that the change semantic information is first determined based on the change image point information, that is, the specific change content of the changed picture area or image area, such as: character movement, light and shadow changes, scenery addition, etc., so that the specific adjustment strategy can be determined based on the change semantic information.

[0078] In a specific implementation, after the adjustment strategy is determined, the specific adjustment strategy for the image points that need to be adjusted in the preliminary imaging image is determined according to the adjustment strategy. For example, if a person moves, the middle position of the person's movement is selected, and then the contour is clarified.

[0079] Furthermore, in order to accurately determine the adjustment strategy, the step of determining the adjustment strategy of the preliminary imaging image according to the change semantic information includes: determining the imaging change scene according to the change semantic information; determining the imaging modification strategy according to the imaging change scene; determining the adjustment strategy of the preliminary imaging image according to the imaging modification strategy.

[0080] It should be noted that after determining the change semantic information, the imaging change scene is first determined according to the change semantic information, that is, to determine which scene the specific change belongs to, including but not limited to character movement, light and shadow change, and scenery addition.

[0081] It should be understood that after the imaging change scenario is determined, the imaging modification strategy is determined based on the difference in the imaging change scenario.

[0082] In the specific implementation, when the imaging change scene is the movement of a person, the imaging modification strategy is to determine the starting point and end point of the person's movement, and then take the middle position of the person's movement as the reference, and then clarify the contour, and clearly fix the person's contour with width or trailing shadow in the middle position, thereby achieving clarity of dynamic imaging.

[0083] It should be noted that when the imaging change scene is a light and shadow change, the imaging modification strategy is to first determine the target brightness value, and then adjust the brightness, contrast, etc. of all image points to the target value, so as to achieve clarity of dynamic imaging.

[0084] It should be understood that when the imaging change scene is the addition of scenery, the imaging modification strategy is to determine the added scenery and the position and layer of the added scenery. The layer is the occlusion relationship between the added scenery and other objects, so that the image corresponding to the added scenery can be directly generated in the preliminary imaging image, realizing dynamic imaging.

[0085] This embodiment determines the fitting image data according to the dynamic sensor data; compares the fitting image data with the preliminary imaging image, and optimizes the preliminary imaging image according to the comparison result to obtain a dynamic imaging image. In this way, the image that has been imaged is optimized and adjusted with the next cycle data as a reference, and the unclear or defective image areas in the preliminary image are actively removed, so that the dynamic imaging image is clearer and the effect is better.

[0086] In addition, an embodiment of the present invention further provides a storage medium, on which a dynamic computational imaging program is stored. When the dynamic computational imaging program is executed by a processor, the steps of the dynamic computational imaging method described above are implemented.

[0087] Since the storage medium adopts all the technical solutions of all the above embodiments, it has at least all the beneficial effects brought by the technical solutions of the above embodiments, which will not be described one by one here.

[0088] Reference Figure 4 , Figure 4 It is a structural block diagram of the first embodiment of the dynamic computational imaging device of the present invention.

[0089] like Figure 4 As shown, the dynamic computational imaging device proposed in the embodiment of the present invention includes:

[0090] The data acquisition module 10 is used to acquire imaging sensor data and dynamic sensor data, wherein the dynamic sensor data is frame data of the imaging sensor data in the next time period.

[0091] The preliminary generating module 20 is used to generate a preliminary imaging image according to the imaging sensor data.

[0092] The dynamic imaging module 30 is used to optimize the preliminary imaging image according to the dynamic sensor data to obtain a dynamic imaging image.

[0093] In one embodiment, the data acquisition module 10 is also used to collect sensor data; split the sensor data into multiple groups of frame data according to a preset cycle length; and extract imaging sensor data and dynamic sensor data from each group of frame data according to the current cycle.

[0094] In one embodiment, the preliminary generation module 20 is further used to obtain image point data based on the imaging sensor data; determine imaging point position information and imaging point color information based on the image point data; and generate a preliminary imaging image based on the imaging point position information and the imaging point color information.

[0095] In one embodiment, the dynamic imaging module 30 is further used to determine fitting image data according to the dynamic sensor data; compare the fitting image data with the preliminary imaging image, and optimize the preliminary imaging image according to the comparison result to obtain a dynamic imaging image.

[0096] In one embodiment, the dynamic imaging module 30 is further used to determine the dynamic information of the image point based on the fitting image data; compare the dynamic information of the image point with the preliminary imaging image; obtain the changed image point information based on the comparison result; optimize the preliminary imaging image based on the changed image point information to obtain the dynamic imaging image.

[0097] In one embodiment, the dynamic imaging module 30 is further used to determine change semantic information based on the change image point information; determine an adjustment strategy for the preliminary imaging image based on the change semantic information; and adjust the image points in the preliminary imaging image using the adjustment strategy to obtain a dynamic imaging image.

[0098] In one embodiment, the dynamic imaging module 30 is further used to determine an imaging change scene according to the change semantic information; determine an imaging modification strategy according to the imaging change scene; and determine an adjustment strategy for the preliminary imaging image according to the imaging modification strategy.

[0099] This embodiment acquires imaging sensor data and dynamic sensor data, wherein the dynamic sensor data is the frame data of the next time period of the imaging sensor data; generates a preliminary imaging image according to the imaging sensor data; and optimizes the preliminary imaging image according to the dynamic sensor data to obtain a dynamic imaging image. In this way, it is achieved that frame data at two moments are collected during imaging, and then the image imaged by the current cycle data is optimized based on the frame data of the next cycle, thereby achieving dynamic imaging and improving image quality.

[0100] It should be understood that the above is only an example and does not constitute any limitation on the technical solution of the present invention. In specific applications, technicians in this field can make settings as needed, and the present invention does not limit this.

[0101] It should be noted that the workflow described above is merely illustrative and does not limit the scope of protection of the present invention. In practical applications, technicians in this field can select part or all of them according to actual needs to achieve the purpose of the present embodiment, and no limitation is made here.

[0102] The present application provides a computer-readable storage medium having computer-readable program instructions (ie, computer programs) stored thereon, and the computer-readable program instructions are used to execute the dynamic computational imaging method in the above-mentioned embodiment.

[0103] The computer-readable storage medium provided in the present application may be, for example, a USB flash drive, but is not limited to electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, systems or devices, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this embodiment, the computer-readable storage medium may be any tangible medium containing or storing a program that can be used by or in combination with an instruction execution system, system or device. The program code contained on the computer-readable storage medium may be transmitted using any appropriate medium, including but not limited to: wires, optical cables, RF (Radio Frequency), etc., or any suitable combination of the above.

[0104] The computer-readable storage medium may be included in the dynamic computing imaging device; or may exist independently without being assembled into the device.

[0105] Computer program code for performing the operations of the present application may be written in one or more programming languages ​​or a combination thereof, including object-oriented programming languages ​​such as Java, Smalltalk, C++, and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the user's computer, partially on the user's computer, as a separate software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider).

[0106] The flow chart and block diagram in the accompanying drawings illustrate the possible architecture, function and operation of the system, method and computer program product according to various embodiments of the present application. In this regard, each square box in the flow chart or block diagram can represent a module, a program segment or a part of a code, and the module, the program segment or a part of the code contains one or more executable instructions for realizing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the square box can also occur in a sequence different from that marked in the accompanying drawings. For example, two square boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each square box in the block diagram and / or flow chart, and the combination of the square boxes in the block diagram and / or flow chart can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0107] The modules involved in the embodiments described in this application may be implemented by software or hardware, wherein the name of the module does not constitute a limitation on the unit itself in some cases.

[0108] The readable storage medium provided in the present application is a computer-readable storage medium, which stores computer-readable program instructions (i.e., computer programs) for executing the above-mentioned dynamic computational imaging method, and can solve the technical problem that the imaging is easily blurred or the effect is poor. Compared with the prior art, the beneficial effects of the computer-readable storage medium provided in the present application are the same as the beneficial effects of the dynamic computational imaging method provided in the above-mentioned embodiment, and will not be repeated here.

[0109] The present application also provides a computer program product, comprising a computer program, wherein when the computer program is executed by a processor, the steps of the dynamic computational imaging method as described above are implemented.

[0110] The computer program product provided by the present application can solve the technical problem that the imaging is easily blurred or the effect is poor. Compared with the prior art, the beneficial effects of the computer program product provided by the present application are the same as the beneficial effects of the dynamic computational imaging method provided by the above embodiment, which will not be repeated here.

[0111] The above descriptions are only some embodiments of the present application, and are not intended to limit the patent scope of the present application. All equivalent structural changes made using the contents of the present application specification and drawings under the technical concept of the present application, or direct / indirect applications in other related technical fields are included in the patent protection scope of the present application.

Claims

1. A dynamic computational imaging method, characterized in that: The dynamic computational imaging method comprises: Acquire imaging sensor data and dynamic sensor data, wherein the dynamic sensor data is frame data of the imaging sensor data in the next time period; generating a preliminary imaging image based on the imaging sensor data; Determining fitting image data according to the dynamic sensor data; Determine image point dynamic information according to the fitted image data, wherein the image point dynamic information refers to image point information in the fitted image data having a color change compared with the preliminary image; Comparing the image point dynamic information with the preliminary imaging image; Obtaining changed image point information according to the comparison result, wherein the changed image point information refers to summary information of image points at the same position where color, contrast or saturation changes occur; Determining change semantic information according to the change image point information; Determining an adjustment strategy for the preliminary image according to the change semantic information; The image points in the preliminary imaging image are adjusted by the adjustment strategy to obtain a dynamic imaging image.

2. The dynamic computational imaging method according to claim 1, characterized in that: The acquiring of imaging sensor data and dynamic sensor data comprises: Collect sensor data; Splitting the sensor data into multiple groups of frame data according to a preset cycle duration; Imaging sensor data and dynamic sensor data are extracted from each set of frame data according to the current cycle.

3. The dynamic computational imaging method according to claim 1, wherein: The step of generating a preliminary imaging image according to the imaging sensor data comprises: Obtaining image point data according to the imaging sensor data; Determine imaging point position information and imaging point color information according to the image point data; A preliminary imaging image is generated according to the imaging point position information and the imaging point color information.

4. The dynamic computational imaging method according to claim 1, wherein: The step of determining the adjustment strategy of the preliminary image according to the change semantic information includes: determining an imaging change scene according to the change semantic information; Determining an imaging modification strategy according to the imaging change scenario; An adjustment strategy for the preliminary image is determined according to the imaging modification strategy.

5. A dynamic computational imaging device, characterized in that: The dynamic computational imaging device comprises: A data acquisition module, used to acquire imaging sensor data and dynamic sensor data, wherein the dynamic sensor data is frame data of the imaging sensor data in the next time period; A preliminary generation module, used to generate a preliminary imaging image according to the imaging sensor data; A dynamic imaging module is used to determine fitting image data based on the dynamic sensor data; determine image point dynamic information based on the fitting image data, the image point dynamic information refers to image point information with color changes between the fitting image data and the preliminary imaging image; compare the image point dynamic information with the preliminary imaging image; obtain change image point information based on the comparison result, the change image point information refers to summary information of image points with color, contrast or saturation changes at the same position; determine change semantic information based on the change image point information; determine an adjustment strategy for the preliminary imaging image based on the change semantic information; adjust the image points in the preliminary imaging image according to the adjustment strategy to obtain a dynamic imaging image.

6. A computer device, characterized in that: The computer device comprises: a memory and a processor, and the processor executes the method according to any one of claims 1 to 4 when running the computer instructions stored in the memory.

7. A readable storage medium, characterized in that: The method comprises instructions, which, when executed on a computer device, cause the computer device to execute the method according to any one of claims 1 to 4.

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