Projection imaging system

Abstract

The invention relates to a projection imaging system and a projection imaging method. The projection imaging system includes: a display configured to receive an image signal and output an image screen; the imaging element is configured to receive an image picture and project, amplify and image the image picture; the controller is configured to perform image processing on an image signal of the image to be projected and output the processed image signal to the display; and the image processing is used for forming an amplified to-be-projected image after the image picture output by the display is projected by the imaging element. According to the projection imaging system, the structure of the projection imaging system can be simplified, and miniaturization and integration of the projection imaging system are facilitated.

Description

Technical Field

[0001] This application relates to the field of projection equipment technology, and in particular to a projection imaging system and projection imaging method. Background Technology

[0002] With the rapid development of technology, a projection imaging system can be constructed by integrating imaging elements behind the display screen to achieve magnified imaging of images.

[0003] Generally, a projection imaging system includes a display screen and a projection lens. To achieve clear projection imaging, multiple imaging elements are usually superimposed behind the display screen to form the required projection lens. This results in a limited size of the projection system, making it difficult to miniaturize and integrate.

[0004] Therefore, there is an urgent need for a miniaturized and integrated projection imaging system. Summary of the Invention

[0005] This application provides a projection imaging system and projection imaging method to solve the problem that traditional projection imaging systems are limited in size and not convenient for miniaturization and integration.

[0006] In a first aspect, some embodiments provide a projection imaging system, including:

[0007] The display is configured to receive image signals and output image frames;

[0008] An imaging element is configured to receive an image and project and magnify the image.

[0009] The controller is configured to perform image processing on the image signal of the image to be projected and output the processed image signal to the display. The image processing is used to: make the image output by the display be projected by the imaging element to form an enlarged image to be projected.

[0010] The aforementioned projection imaging system includes a display that does not require an additional light source. It can process the image signal of the image to be projected via a controller and output the processed image signal to the display. The image processing ensures that the image output from the display is projected through an imaging element to form a magnified image to be projected. In other words, image processing guarantees the projection effect of the image output from the display. Based on this, after the display receives the processed image signal and outputs the desired image, the imaging element receives the image and projects it to form a magnified image to be projected. Using this projection imaging system, the controller can process the image to be projected, ensuring that after the display receives the processed image signal, the image output from the display is projected and magnified through the imaging element to form a magnified image of the image to be projected. This simplifies the structure of the projection imaging system, facilitating its miniaturization and integration, unlike traditional projection imaging systems that rely on complex projection lenses.

[0011] Secondly, some embodiments provide yet another projection imaging system, including:

[0012] The tri-color illumination source is configured to emit an illumination beam;

[0013] The display is configured to receive image signals and illumination beams, and to output image images;

[0014] An imaging element is configured to receive an image and project and magnify the image.

[0015] The controller is configured to perform image processing on the image signal of the image to be projected and output the processed image signal to the display. The image processing is used to: make the image output by the display be projected by the imaging element to form an enlarged image to be projected.

[0016] The aforementioned projection imaging system includes a display that requires an additional light source. A controller can process the image signal of the image to be projected and output the processed image signal to the display. Image processing ensures that the image output from the display is projected through an imaging element to form a magnified image to be projected. Furthermore, a tri-color illumination source can emit an illumination beam to provide light to the display. The display can then receive the processed image signal and the illumination beam, output the desired image, and the imaging element receives and magnifies the image to form the magnified image to be projected. Using this projection imaging system, the controller can process the image to be projected, ensuring that after the display receives the processed image signal, the image output from the display is projected and magnified through the imaging element to form the magnified image to be projected. This simplifies the structure of the projection imaging system, facilitating its miniaturization and integration, unlike traditional projection imaging systems that rely on complex projection lenses.

[0017] Thirdly, some embodiments also provide a projection imaging method applied to the projection imaging system provided in the first aspect, the method comprising:

[0018] The image signal of the image to be projected is processed, and the processed image signal is output to the display. The image processing is used to: make the image output by the display be projected by the imaging element to form an enlarged image to be projected.

[0019] The system receives the processed image signal from the display and outputs the image.

[0020] The imaging element receives the image and projects and magnifies it into a final image.

[0021] Fourthly, some embodiments also provide a projection imaging method applied to the projection imaging system provided in the second aspect, the method comprising:

[0022] The image signal of the image to be projected is processed, and the processed image signal is output to the display. The image processing is used to: make the image output by the display be projected by the imaging element to form an enlarged image to be projected.

[0023] The system emits a beam of light through a three-color illumination source, receives the beam of light and the processed image signal through a display, and outputs the image.

[0024] The imaging element receives the image and projects and magnifies it into a final image.

[0025] Fifthly, some embodiments also provide a projection imaging apparatus applied to the projection imaging system provided in the first aspect, the apparatus comprising:

[0026] The image signal processing module is used to process the image signal of the image to be projected and output the processed image signal to the display. The image processing is used to: make the image output by the display be projected by the imaging element to form an enlarged image to be projected.

[0027] The image output module is used to receive the processed image signal through the display and output the image.

[0028] The image projection module is used to receive images through the imaging element and project and magnify the images.

[0029] Sixthly, some embodiments also provide a projection imaging apparatus applied to the projection imaging system provided in the second aspect, the apparatus comprising:

[0030] The image signal processing module is used to process the image signal of the image to be projected and output the processed image signal to the display. The image processing is used to: make the image output by the display be projected by the imaging element to form an enlarged image to be projected.

[0031] The image output module is used to emit an illumination beam through a three-color illumination source, receive the illumination beam and the processed image signal through a display, and output the image.

[0032] The image projection module is used to receive images through the imaging element and project and magnify the images.

[0033] In a seventh aspect, some embodiments also provide a computer-readable storage medium. The computer-readable storage medium stores a computer program thereon, which, when executed by a processor, implements the projection imaging method provided in the third or fourth aspect.

[0034] Eighthly, some embodiments also provide a computer program product. The computer program product includes a computer program that, when executed by a processor, implements the projection imaging method provided in the third or fourth aspect.

[0035] The above-mentioned projection imaging method, device, computer-readable storage medium and computer program product can process the image to be projected through the controller, and ensure that after the display receives the processed image signal, the image output by the display is projected and magnified by the imaging element to form the magnified image to be projected, instead of relying on the complex structure of the projection lens in the traditional projection imaging system. This simplifies the structure of the projection imaging system and is conducive to the miniaturization and integration of the projection imaging system. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0037] Figure 1 A schematic diagram illustrating the operational scenarios between a projection imaging system and a control device provided in some embodiments of this application;

[0038] Figure 2 This is a schematic diagram of the hardware configuration of a projection imaging system provided in some embodiments of this application;

[0039] Figure 3 A schematic diagram of the functional module architecture of a projection imaging system including an active display, provided for some embodiments of this application;

[0040] Figure 4 A schematic diagram of the functional module architecture of a projection imaging system including a passive display provided for some embodiments of this application;

[0041] Figure 5 This is a timing diagram of the internal processing of the image to be projected in a projection imaging system according to one embodiment of this application;

[0042] Figure 6 This is a schematic diagram of the functional module architecture of a projection imaging system including a first optical path adjustment element in one embodiment of this application;

[0043] Figure 7 This is a schematic diagram of the functional module architecture of a projection imaging system including a second optical path adjustment element in one embodiment of this application;

[0044] Figure 8 This is an interactive flowchart of the controller of the projection imaging system in one embodiment of the present application determining the target pre-distortion processing parameters;

[0045] Figure 9This is a schematic diagram of a projection imaging system architecture that combines a monolithic diffractive lens and an active microdisplay to achieve projection display in one embodiment of this application.

[0046] Figure 10 This is a schematic diagram of a projection imaging system architecture that combines a monolithic optical lens and an active microdisplay to achieve projection display in one embodiment of this application.

[0047] Figure 11 This is a schematic diagram of a projection imaging system architecture that combines a transmissive metalens and an active microdisplay to achieve projection display in one embodiment of this application.

[0048] Figure 12 This is a schematic diagram of a projection imaging system architecture that combines a transmissive phase modulator and an active microdisplay to achieve projection display in one embodiment of this application.

[0049] Figure 13 This is a schematic diagram of a projection imaging system architecture that combines a monolithic diffractive mirror and an active microdisplay to achieve projection display in one embodiment of this application.

[0050] Figure 14 This is a schematic diagram of a projection imaging system architecture that combines a monolithic optical mirror and an active microdisplay to achieve projection display in one embodiment of this application.

[0051] Figure 15 This is a schematic diagram of a projection imaging system architecture that combines a reflective metalens and an active microdisplay to achieve projection display in one embodiment of this application.

[0052] Figure 16 This is a schematic diagram of a projection imaging system architecture that combines a reflective phase modulator and an active microdisplay to achieve projection display in one embodiment of this application.

[0053] Figure 17 This is a schematic diagram of a projection imaging system architecture that combines a monolithic diffractive lens and a passive microdisplay to achieve projection display in one embodiment of this application.

[0054] Figure 18 This is a schematic diagram of a projection imaging system architecture that combines a monolithic optical lens and a passive microdisplay to achieve projection display in one embodiment of this application.

[0055] Figure 19 This is a schematic diagram of a projection imaging system architecture that combines a transmissive meta-lens and a passive micro-display in one embodiment of this application to achieve projection display;

[0056] Figure 20 This is a schematic diagram of a projection imaging system architecture that combines a transmissive phase modulator and a passive microdisplay to achieve projection display in one embodiment of this application.

[0057] Figure 21 This is a schematic diagram of a projection imaging system architecture that combines a monolithic diffractive mirror and a passive microdisplay to achieve projection display in one embodiment of this application.

[0058] Figure 22 This is a schematic diagram of a projection imaging system architecture that combines a monolithic optical mirror and a passive microdisplay to achieve projection display in one embodiment of this application.

[0059] Figure 23 This is a schematic diagram of a projection imaging system architecture that combines a reflective metalens and a passive microdisplay to achieve projection display in one embodiment of this application.

[0060] Figure 24 This is a schematic diagram of a projection imaging system architecture that combines a reflective phase modulator and a passive microdisplay to achieve projection display in one embodiment of this application.

[0061] Figure 25 Interactive flowcharts of projection imaging methods provided in some embodiments of this application;

[0062] Figure 26 The interactive flowchart is provided for some other embodiments of the projection imaging method provided in this application. Detailed Implementation

[0063] The embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings represent the same or similar elements. The embodiments described below do not represent all embodiments consistent with this application. They are merely examples of systems and methods consistent with some aspects of this application as detailed in the claims.

[0064] It should be noted that the brief descriptions of terms in this application are only for the convenience of understanding the embodiments described below, and are not intended to limit the embodiments of this application. Unless otherwise stated, these terms should be understood in their ordinary and common meaning.

[0065] The terms "first," "second," "third," etc., used in the specification, claims, and accompanying drawings of this application are used to distinguish similar or related objects or entities, and do not necessarily imply a specific order or sequence, unless otherwise specified. It should be understood that such terms are interchangeable where appropriate.

[0066] The terms “comprising” and “having”, and any variations thereof, are intended to cover but not exclude inclusion, for example, a product or device that includes a range of components is not necessarily limited to all of the components that are clearly listed, but may include other components that are not clearly listed or that are inherent to such product or device.

[0067] The term "module" refers to any known or subsequently developed hardware, software, firmware, artificial intelligence, fuzzy logic, or combination of hardware and / or software code that is capable of performing the functions associated with that element.

[0068] Figure 1 This is a schematic diagram illustrating the operational scenarios between a projection imaging system and a control device provided in some embodiments of this application. For example... Figure 1 As shown, a user can operate the projection imaging system 200 via touch operation, a mobile terminal 300, and a control device 100. For example, the control device 100 can be a remote control, a stylus, a handle, etc.

[0069] In this embodiment, the projection imaging system 200 generally refers to a device with image projection and data processing capabilities. For example, the projection imaging system 200 includes, but is not limited to, projectors, smart TVs, mobile terminals, computers, monitors, advertising screens, wearable devices, virtual reality devices, and augmented reality devices. The mobile terminal 300 can serve as a control device for performing human-computer interaction between the user and the projection imaging system 200. The mobile terminal 300 can also serve as a communication device for establishing a communication connection with the projection imaging system 200 and performing data interaction.

[0070] In some embodiments, the mobile terminal 300 can install software applications with the projection imaging system 200 to establish a connection and communication via a network communication protocol, thereby achieving one-to-one control operation and data communication. Alternatively, the audio and video content displayed on the mobile terminal 300 can be transmitted to the projection imaging system 200 to achieve synchronous projection.

[0071] like Figure 1 The diagram also shows that the projection imaging system 200 communicates with the server 400 via various communication methods. The projection imaging system 200 can communicate via a local area network (LAN), a wireless local area network (WLAN), and other networks.

[0072] The projection imaging system 200 can provide broadcast television reception functions, and can also be equipped with intelligent network television functions that provide computer support, including but not limited to network television, smart television, Internet Protocol television (IPTV), etc.

[0073] Figure 2 Provided for some embodiments of this application Figure 1 Hardware configuration block diagram of the projection imaging system 200.

[0074] In some embodiments, the projection imaging system 200 may include at least one of a tuner 210, a communication device 220, a detector 230, a device interface 240, a controller 250, a display 260, an audio output device 270, an imaging element 280, a memory, a power supply, and a user input interface 290.

[0075] In some embodiments, detector 230 is used to acquire signals from the external environment or to interact with the outside world. For example, detector 230 includes a light receiver, a sensor for acquiring ambient light intensity; or, detector 230 includes an image acquisition device, such as a camera, which can be used to acquire images to be projected, external environmental scenes, user attributes, or user interaction gestures; or, detector 230 includes a sound acquisition device, such as a microphone, for receiving external sounds.

[0076] In some embodiments, the display 260 includes display function components for presenting images and driving components for driving image display. The display 260 is used to receive and display image signals output from the controller 250. For example, the display 260 can be used to display video content, image content, menu control interface components, and user control UI interfaces, etc. In some optional embodiments, the projection imaging system 200 may further include a touch component connected to the display 260, which may be a touchpad, touch screen, etc.

[0077] In some embodiments, the communication device 220 is a component used to communicate with external devices or the server 400 according to various communication protocol types. The projection imaging system 200 may have multiple communication devices 220 depending on the supported communication methods. For example, when the projection imaging system 200 supports wireless network communication, it may have a communication device 220 with WiFi functionality. When the projection imaging system 200 supports Bluetooth connectivity, it needs to have a communication device 220 with Bluetooth functionality.

[0078] The communication device 220 enables the projection imaging system 200 to communicate with external devices or the server 400 via wireless or wired connections. Wired connections utilize data cables, interfaces, or other components to connect the projection imaging system 200 to external devices. Wireless connections utilize wireless signals or wireless networks. The projection imaging system 200 can establish a direct connection with external devices or indirectly through gateways, routers, or other connection devices.

[0079] In some embodiments, the controller 250 may include at least one of a central processing unit, a video processor, an audio processor, a graphics processor, and a power processor, and a first to an nth interface for input / output. The controller 250 controls the operation of the display device and responds to user operations through various software control programs stored in memory. The controller 250 controls the overall operation of the projection imaging system 200.

[0080] In some embodiments, the controller 250 and the tuner 210 may be located in different separate devices, that is, the tuner 210 may also be located in an external device of the main device where the controller 250 is located, such as an external set-top box.

[0081] In some embodiments, the imaging element 280 is specifically an optical element, which may include at least one of a diffractive imaging element, a projection imaging element, a reflective imaging element, and an optical phase modulator, for projecting and magnifying the image displayed on the display 260.

[0082] In some embodiments, a user can input user commands through a graphical user interface (GUI) displayed on a display 260, and the user input interface receives user input commands through the graphical user interface (GUI).

[0083] In some embodiments, the audio output device 270 can be a built-in speaker of the projection imaging system 200 or an external audio output device connected to the projection imaging system 200. For the external audio output device connected to the projection imaging system 200, the projection imaging system 200 may also be provided with an external audio output terminal, through which the audio output device can be connected to the projection imaging system 200 to output sound from the projection imaging system 200.

[0084] In some embodiments, the user input interface 290 can be used to receive instructions from user input.

[0085] In the above application environments, to simplify the structure of the projection imaging system and achieve its miniaturization and integration, some embodiments provide a projection imaging system that can achieve clear projection imaging without relying on complex projection lenses. Specifically, using the above-mentioned projection imaging system, the image signal of the image to be projected can be processed by the controller. This ensures that after the display receives the processed image signal, the image output by the display is projected and magnified by the imaging element to form the magnified image to be projected, instead of relying on complex projection lenses as in traditional projection imaging systems. This simplifies the structure of the projection imaging system and facilitates its miniaturization and integration.

[0086] In some embodiments, such as Figure 3 As shown, a projection imaging system including an active display is provided, wherein the active display does not require an additional light source. Specifically, the projection imaging system includes: a display 310 configured to receive image signals and output image images; an imaging element 320 configured to receive image images and project and enlarge them into an image; and a controller 330 configured to perform image processing on the image signal of the image to be projected and output the processed image signal to the display 310; the image processing is used to: cause the image image output by the display 310 to be projected by the imaging element 320 to form an enlarged image to be projected.

[0087] In some embodiments, such as Figure 4 As shown, a projection imaging system including a passive display is provided, wherein the passive display requires an additional light source. Specifically, the projection imaging system includes: a tri-color illumination source 410 configured to emit an illumination beam; a display 420 configured to receive an image signal and the illumination beam, and output an image; an imaging element 430 configured to receive the image and project and magnify it; and a controller 440 configured to perform image processing on the image signal of the image to be projected, and output the processed image signal to the display 420. The image processing is used to: ensure that the image output by the display 420 is projected by the imaging element 430 to form a magnified image to be projected.

[0088] in, Figure 3 or Figure 4 The image to be projected can be at least one discontinuous image or a series of multiple consecutive images (i.e., the video to be projected). Figure 3 or Figure 4 The imaging element can be a single element or a combination of a small number of elements.

[0089] Optionally, regarding Figure 3 or Figure 4 The acquisition methods for the image to be projected include at least the following: the user transmits image data to the device interface of the projection imaging system through the control device; the user inputs an image acquisition command through the user input interface of the projection imaging system, so that the image acquisition device of the projection imaging system can acquire the image to be projected; if the display of the projection imaging system can also display application identifiers related to image acquisition, the user can select the corresponding application identifier to trigger the image acquisition command, so that the image acquisition device of the projection imaging system can acquire the image to be projected; the user triggers the image acquisition command through voice through the sound acquisition device of the projection imaging system, so that the image acquisition device of the projection imaging system can acquire the image to be projected.

[0090] For example, the display can specifically be a device for displaying images, text, and colors, such as a microdisplay, including but not limited to Micro LED displays, DMD displays, LCoS displays, etc., and the display can be either an active microdisplay or a passive microdisplay. Active microdisplays do not require an additional light source; after receiving an image signal, they emit light according to the brightness distribution of the image signal, outputting a projectable image with sufficient brightness. Passive microdisplays, on the other hand, require an additional light source; after receiving the light source and the image signal, they output a projectable image based on the brightness distribution of the image signal and the three colors of light in the light source. In this embodiment, the display can receive the image signal processed by the controller, output a projectable image, and then project and enlarge the image through an imaging element to form an enlarged image to be projected.

[0091] Optionally, the imaging element can be a component used to control light transmission and processing. Its material is typically optical glass, crystal, semiconductor, etc., and it can be classified into various types according to its function and structural characteristics, such as diffraction imaging elements, transmission imaging elements, reflection imaging elements, optical phase modulators, etc. In this embodiment, the imaging element can be a simple single-sided mirror, a single lens, a metalens, a phase modulator, etc.

[0092] For example, the controller can be a device capable of integrating complex processing logic, including but not limited to FPGA (Field-Programmable Gate Array), GPU (Graphics Processing Unit), CPU (Central Processing Unit), etc. In this embodiment, an image processing model can be deployed on the controller to process the image signal of the image to be projected, ensuring the projection effect of the image output by the display. This allows the image output by the display to be magnified and projected by the imaging element after receiving the processed image signal, thus forming the magnified image of the image to be projected.

[0093] In some embodiments, based on the above Figure 3 or Figure 4 Projection imaging systems in, such as Figure 5As shown, a timing diagram of the internal processing of the image to be projected in the projection imaging system is provided. Specifically, after acquiring the image signal of the image to be projected, the controller can first process the image signal of the image to be projected, and then output the processed image signal to the display. The display can then further output an image based on the received image signal. Finally, the image output by the display is projected by the imaging element to form a magnified image to be projected.

[0094] The above technical solution has the following advantages or beneficial effects: By using the above projection imaging system (whether or not it includes an active microdisplay or a passive microdisplay), the image processing of the image to be projected can be achieved through the controller. This ensures that after the display receives the processed image signal, the image output by the display is projected and magnified by the imaging element to form the magnified image of the image to be projected. Instead of relying on the complex structure of the projection lens in the traditional projection imaging system, this simplifies the structure of the projection imaging system and is conducive to the miniaturization and integration of the projection imaging system.

[0095] In some embodiments, with Figure 4 The example shown is a projection imaging system including a passive display, such as... Figure 6 The diagram shows a functional module architecture of a projection imaging system including a first optical path adjustment element 450. Specifically, the first optical path adjustment element 450 is configured to adjust the projection optical path of the illumination beam so that the display 420 receives the illumination beam.

[0096] Specifically, the first optical path adjustment element 450 can be an optical element with light reflection function, such as various mirrors, which can use reflection to adjust the optical path. There can be at least one first optical path adjustment element 450, and its size can be flexibly set according to the size requirements of the projection imaging system.

[0097] The above technical solution has the following advantages or beneficial effects: Considering that when designing a projection imaging system including a passive display, it may be impossible to ensure that the illumination beam emitted by the three-color illumination source 410 can be directly projected onto the display 420, it is possible to add a first optical path adjustment element 450 to the projection imaging system to ensure that the illumination beam emitted by the three-color illumination source 410 can be projected onto the display 420, and to ensure that the display 420 can use the provided light source to output a bright and projectable image.

[0098] In some embodiments, with Figure 6 The example shown is a projection imaging system including a passive display, such as... Figure 7The diagram shows a functional module architecture of a projection imaging system including a second optical path adjustment element 460. Specifically, the second optical path adjustment element 460 is configured to adjust the projection optical path of the image frame so that the imaging element 430 receives the image frame.

[0099] Specifically, the second optical path adjustment element 460 can be an optical element with light reflection function, such as various mirrors, which can use reflection to adjust the optical path. The number of second optical path adjustment elements 460 can be at least one, and their size can be flexibly set according to the size requirements of the projection imaging system.

[0100] The above technical solution has the following advantages or beneficial effects: Considering that when designing a projection imaging system including a passive display, there may be situations where the image output by the display 420 cannot be directly projected onto the imaging element 430, it is possible to add a second optical path adjustment element 460 to the projection imaging system to ensure that the image output by the display 420 can be projected onto the imaging element 430, thereby ensuring that the imaging element 430 can project an image.

[0101] In some embodiments, when the controller performs the step of image processing on the image signal of the image to be projected, it is further configured to: obtain the target point spread function of the imaging element and the target projection ratio set for the projection imaging system; determine the target pre-distortion processing parameters according to the target point spread function and the target projection ratio, and update the pre-distortion processing parameters of the pre-distortion processing model using the target pre-distortion processing parameters to obtain the updated pre-distortion processing model; and perform image processing on the image signal of the image to be projected using the updated pre-distortion processing model to obtain the processed image signal.

[0102] The projection ratio specifically refers to the ratio of the projection distance to the width of the projected image. In this embodiment, the target projection ratio can be a personalized projection ratio set by the user according to the desired projection display effect. The point spread function (PSF) is a function that characterizes the response of an imaging element to a point light source. It is related to the structure of the imaging element. For an imaging element, if the input object is a point light source, the light field distribution of the output image can be called the point spread function of the imaging element. The pre-distortion processing model is a neural network model that can process images according to preset parameters. The specific network structure of this pre-distortion processing model is not unique and can include fully connected neural networks (FCNN), convolutional neural networks (CNN), recurrent neural networks (RNN), or deep neural networks (DNN), etc. The controller can store a pre-distortion processing model and a table / document / file storing the mapping relationship between the element parameters of the imaging element and the point spread function. The controller can control the pre-distortion processing model to update the pre-distortion processing parameters and control the updated pre-distortion processing model to process the image to be projected.

[0103] Optionally, the imaging element in this embodiment can be a simple optical element. Therefore, for each imaging element, the point spread function of the imaging element can be pre-calculated when the input object is a point light source, and the measured point spread function is stored in the controller for subsequent acquisition by the controller. In subsequent applications, even if the structure of the imaging element in the projection imaging system is simple (without the need to use multiple imaging elements superimposed as in traditional technologies), the controller can process the image to be projected into a pre-distorted image that matches both the target point spread function of the imaging element and the target projection ratio set by the user through a pre-distortion processing model. After the pre-distorted image is loaded and displayed on the display, it can be projected and magnified by a simple imaging element to form a clear projected image at the target projection ratio (i.e., the specified projection ratio). Specifically, the controller can determine the target pre-distortion processing parameters based on the target point spread function and the target projection ratio, and use the target pre-distortion processing parameters to update the pre-distortion processing parameters of the pre-distortion processing model, thereby obtaining the updated pre-distortion processing model. Then, the updated pre-distortion processing model is used to perform image processing (i.e., pre-distortion processing) on ​​the projected image to obtain the processed image (i.e., the pre-distortion processed image).

[0104] The above technical solution has the following advantages or beneficial effects: Given that the target point spread function of the imaging element is known, the above projection imaging system can adjust the projection ratio for any target projection ratio set by the user without replacing the imaging element. Instead, it can flexibly update the pre-distortion processing parameters of the pre-distortion processing model according to the target projection ratio. Through the updated pre-distortion processing model, the image to be projected is processed into a pre-distorted image that matches both the target point spread function and the target projection ratio. After the display receives the pre-distorted image and outputs the image, this image is projected by the imaging element to form a clear image at the target projection ratio. In other words, without relying on the replacement or adjustment of physical components, the projection ratio can be adjusted by adjusting the parameters of the pre-distortion processing model (software adjustment only). This not only reduces the increased cost and operation time caused by replacing physical components but also greatly improves the flexibility of the projection imaging system, enabling efficient adjustment of the projection ratio and thus efficiently adjusting the projection display effect.

[0105] In some embodiments, the controller may include a first processor and a second processor. Specifically, the first processor is configured to determine target pre-distortion processing parameters based on the target point spread function and the target projection ratio, and use the target pre-distortion processing parameters to update the pre-distortion processing parameters of the pre-distortion processing model in the second processor. The second processor is configured to perform image processing on the image signal of the projected image using the updated pre-distortion processing model to obtain a processed image signal.

[0106] Optionally, the first and second processors can be processors of different types or the same type, capable of implementing complex processing logic, including but not limited to FPGAs, GPUs, and CPUs. Considering that image processing using the running model consumes significant runtime resources, the pre-distortion processing model can be integrated separately onto one of the processors, i.e., integrated onto the second processor, to ensure its stable operation, while other functions can be integrated onto the first processor. Based on this, in application, the first processor can query and determine the matching target pre-distortion processing parameters based on the obtained target point spread function and target projection ratio, and send a parameter switching command to the second processor. This causes the second processor to update the pre-distortion processing parameters of the pre-distortion processing model to the target pre-distortion processing parameters, and then process the image signal of the image to be projected based on the updated pre-distortion processing model, and output the pre-distorted image signal to the display. It should be noted that the functional integration methods in the controller include, but are not limited to, the integration methods described above that integrate onto one or two devices, and the integration scheme can be flexibly designed according to actual needs.

[0107] The above technical solution has the following advantages or beneficial effects: By integrating the pre-distortion processing model onto a separate processor, the image processing efficiency and operational stability of the pre-distortion processing model can be improved, thereby ensuring that in subsequent applications, the projection ratio can be efficiently adjusted by flexibly switching the pre-distortion processing parameters of the pre-distortion processing model.

[0108] In some embodiments, when the controller performs the step of obtaining the target point spread function of the imaging element, it is further configured to: obtain the target element parameters of the imaging element; and in the mapping relationship between the element parameters and the point spread function, find the point spread function that matches the target element parameters to obtain the target point spread function of the imaging element.

[0109] Specifically, the component parameters can include structural parameters such as the surface shape and size of the imaging element. Different component parameters result in different structures for the imaging element, leading to different responses to point light sources, and consequently, different point spread functions. The target component parameters for the imaging element in a projection imaging system can be stored in the controller as factory-set parameters or entered by the user. For commonly used, simple-structured imaging elements, the point spread function can be pre-calculated, and a mapping relationship between the component parameters and the point spread function can be established and stored in the controller for later use.

[0110] Optionally, taking the integration of controller functions into a single processor as an example, the controller can first obtain the target element parameters of the imaging element in its projection imaging system. Then, it can search for a point spread function matching the target element parameters in the mapping relationship between element parameters and point spread functions stored in the controller, thus obtaining the target point spread function of the imaging element. Alternatively, taking the integration of controller functions into multiple processors as an example, such as a second processor integrating a pre-distortion processing model and a first processor integrating other functions, the first processor can obtain the target element parameters of the imaging element. Then, it can search for a point spread function matching the target element parameters in the mapping relationship between element parameters and point spread functions stored in the first processor, thus obtaining the target point spread function of the imaging element.

[0111] It should be noted that the point spread function of the imaging element can be calculated in the following ways: (1) Direct measurement method: Place a point light source at the input end of the imaging element, and then use the imaging device to record its output image to directly obtain the point spread function of the imaging element. This method is simple and intuitive. (2) Indirect measurement method: Measure the transfer function of the imaging element with the help of an interferometer, and then indirectly calculate the point spread function of the imaging element through the transfer function.

[0112] The above technical solution has the following advantages or beneficial effects: In the application process of a projection imaging system, the target point spread function of the imaging element can be quickly obtained based on the target element parameters of the imaging element in the projection imaging system. This allows for the rapid determination of the target pre-distortion processing parameters based on the target point spread function and the target projection ratio set for the projection imaging system. This ensures that the pre-distorted image obtained after processing by the pre-distortion processing model, after being projected by the imaging element (i.e., after convolution processing by the target point spread function of the imaging element), can form a clear image at the target projection ratio. Therefore, by adopting the above technical solution, it can be ensured that the pre-distorted image obtained is related to the target element parameters of the imaging element in the projection imaging system, so that the pre-distorted image can also be clearly imaged after being projected by an imaging element with a simple structure. That is, it can achieve clear projection imaging without a complex imaging element architecture.

[0113] In some embodiments, when the controller performs the step of obtaining the target projection ratio set for the projection imaging system, it is further configured to: receive a projection ratio setting instruction; and obtain the target projection ratio set for the projection imaging system from the projection ratio setting instruction.

[0114] Specifically, there is more than one way for a user to trigger the throw ratio setting command. If the projection imaging system's display can also show application identifiers related to the throw ratio setting, the user can select the corresponding application identifier to trigger the throw ratio setting command and set the desired throw ratio. If the projection imaging system may include a sound acquisition unit, the user can trigger the throw ratio setting command via voice to set the desired throw ratio.

[0115] Furthermore, taking the integration of controller functions into a single processor as an example, the controller can receive and parse the projection ratio setting instruction to obtain the target projection ratio set by the user for the projection imaging system. Alternatively, taking the integration of controller functions into multiple processors as an example, such as a second processor integrating a pre-distortion processing model and a first processor integrating other functions, the first processor can receive and parse the projection ratio setting instruction to obtain the target projection ratio set by the user for the projection imaging system. Based on the obtained target point spread function and target projection ratio, the appropriate target pre-distortion processing parameters can then be determined.

[0116] The above technical solution has the following advantages or beneficial effects: users can flexibly set the required projection ratio through various channels, and the projection imaging system can update the pre-distortion processing parameters of the pre-distortion processing model according to the target projection ratio set by the user. This updated pre-distortion processing model processes the image to be processed into a pre-distorted image at the target projection ratio. This pre-distorted image, after being displayed on a monitor and then projected onto the imaging element, forms a clear projected image at the target projection ratio. Therefore, adopting the above technical solution can efficiently achieve adjustable projection ratio.

[0117] In some embodiments, such as Figure 8 As shown, a flowchart illustrating the process by which the controller of a projection imaging system determines the target pre-distortion processing parameters is provided. When the controller executes the step of determining the target pre-distortion processing parameters based on the target point spread function and the target projection ratio, it is further configured as follows:

[0118] The predistortion processing model is used to identify multiple candidate predistortion processing parameters; each candidate predistortion processing parameter has its own matching point spread function and projection ratio.

[0119] If among multiple candidate predistortion parameters, there exists a predistortion parameter that matches both the target point spread function and the target projection ratio, then the matching predistortion parameter will be used as the target predistortion parameter.

[0120] If none of the candidate predistortion parameters matches both the target point spread function and the target projection ratio, multiple initial predistortion parameters that match the target point spread function are selected from the candidate parameters. Based on the projection ratio matched by each initial predistortion parameter, a target predistortion parameter that matches both the target point spread function and the target projection ratio is predicted.

[0121] The trained pre-distortion processing model carries pre-distortion processing parameters for each imaging element (each point spread function) at different projection ratios; that is, multiple candidate pre-distortion processing parameters. Currently used projection imaging systems have limited simple imaging element structures. During model training, the point spread function of commonly used simple imaging elements can be largely covered. Even if not, the point spread function of a new simple imaging element can be calculated before its deployment, and the pre-distortion processing parameters for that element can be added to the pre-distortion processing model. However, projection ratios can be continuous, which may result in the pre-distortion processing model not carrying pre-distortion processing parameters that match the target projection ratio during subsequent applications.

[0122] Optionally, taking the integration of functions in the controller into multiple processors as an example, for instance, the second processor integrates a pre-distortion processing model, and the first processor integrates other functions. Then, the first processor can obtain the target point spread function and the target projection ratio, and filter the various candidate pre-distortion processing parameters carried by the pre-distortion processing model integrated in the second processor. That is, it can determine whether there are any candidate pre-distortion processing parameters whose point spread function matches the target point spread function, and whose projection ratio matches the target projection ratio.

[0123] If it exists, the first processor can use the predistortion processing parameters that match the point spread function and projection ratio as the target predistortion processing parameters to achieve rapid acquisition of the target predistortion processing parameters, and instruct the second processor to update the predistortion processing parameters of the predistortion processing model to the target predistortion processing parameters.

[0124] If none exists, the first processor can first select multiple initial predistortion processing parameters that match the target point spread function from a variety of candidate predistortion processing parameters, and then predict the target predistortion processing parameter that matches both the target point spread function and the target projection ratio based on the projection ratio matched by each initial predistortion processing parameter.

[0125] Exemplarily, the first processor can specifically predict the target pre-distortion processing parameters that match both the target point spread function and the target projection ratio in the following ways: (1) Through interpolation, based on the initial pre-distortion processing parameters corresponding to multiple known projection ratios in the target point spread function scenario, estimate the functional relationship between the projection ratio and the initial pre-distortion processing parameters in the target point spread function scenario, so as to predict the target pre-distortion processing parameters corresponding to the unknown projection ratio according to the obtained functional relationship. The finally obtained target pre-distortion processing parameters match both the target point spread function and the target projection ratio. For example, if for the scenario with the point spread function A, the pre-distortion processing parameter theta1 when the projection ratio is r1 and the pre-distortion processing parameter theta2 when the projection ratio is r2 are trained, and the target point spread function of the currently applied display system is also A, but the target projection ratio is r3, and r1 < r3 < r2, then the target pre-distortion processing parameter theta3 corresponding to the target projection ratio r3 can be predicted through the following functional relationship: theta3 = theta1 + (theta2 - theta1) * (r3 - r1) / (r2 - r1) to meet the user's adjustment requirements for continuous projection ratios. (2) Input the initial pre-distortion processing parameters corresponding to multiple known projection ratios under the target point spread function into a learnable parameter adjustment network, so that the parameter adjustment network learns the correlation relationship between the projection ratio and the initial pre-distortion processing parameters, and then outputs the target pre-distortion processing parameters corresponding to the target projection ratio according to the learned correlation relationship. Among them, the parameter adjustment network can be a simple fully connected layer and can be pre-integrated in the first processor.

[0126] It should be noted that if the functions of the controller are not separately integrated, the controller independently executes the above process of determining the target pre-distortion processing parameters.

[0127] The above technical solution has the following advantages or beneficial effects: It can quickly determine the target pre-distortion processing parameters of any target projection ratio under the target point spread function according to the stored pre-distortion processing parameters corresponding to each imaging element (each point spread function) under different projection ratio conditions, so that subsequently, by updating the pre-distortion processing parameters of the pre-distortion processing model, the projection ratio can be quickly adjusted, and clear projection imaging under the target projection ratio can be obtained, without the need to adjust the projection ratio by replacing the imaging element, and the projection display effect of the projection imaging system can be efficiently adjusted.

[0128] It is understandable that by employing the aforementioned projection imaging system, pre-distortion processing of the image to be projected can be performed on the image to be projected. Under a simple imaging element architecture (the dot spread function of the imaging element can be pre-calculated and stored in the controller), clear projection imaging with an adjustable throw ratio can be achieved. Based on this, taking the arbitrary combination of different types of imaging elements with active or passive microdisplays as an example, several schematic diagrams of projection imaging system architectures are provided:

[0129] (1) As Figures 9 to 12 As shown, in Figure 3 Based on the projection imaging system including an active display, a schematic diagram of a projection imaging system architecture combining a transmissive imaging element and an active microdisplay is provided. The controller 330 updates the pre-distortion processing parameters of its pre-distortion processing model based on the target point spread function of the imaging element 320 and the obtained target projection ratio. The updated pre-distortion processing model then processes the image signal of the image to be projected. Furthermore, the controller 330 transmits the processed pre-distortion image signal to the display 310, where it displays the image. The imaging element 320, through transmission, projects and magnifies the image displayed on the display 310, forming a magnified image to be projected. Figures 9 to 12 The active microdisplay shown can emit light (i.e., Micro LED pixelated incoherent light source or Micro LD pixel laser light source) and can generate light with a specific amplitude distribution. When paired with a transmissive imaging element of any simple surface shape, it can achieve clear projection imaging with an adjustable projection ratio. Transmissive imaging elements include, but are not limited to: monolithic diffractive lenses, monolithic optical lenses, transmissive metalenses, and transmissive phase modulators.

[0130] Figure 9 A schematic diagram of a projection imaging system architecture is provided, which combines a monolithic diffractive lens and an active microdisplay to achieve projection display. Figure 9 The transmissive imaging element 320 shown is specifically a monolithic diffractive lens, which can be designed based on a diffractive optical element (DOE). Figure 10 A schematic diagram of a projection imaging system architecture is provided, which combines a monolithic optical lens and an active microdisplay to achieve projection display. Figure 10 The transmissive imaging element 320 shown is specifically a single optical lens, which can be any of the following: spherical lens, aspherical lens, freeform lens, etc. Figure 11 A schematic diagram of a projection imaging system architecture that combines a transmissive metalens and an active microdisplay to achieve projection display is provided. Figure 11The transmissive imaging element 320 shown is specifically a transmissive metalens, which can control light through special shape and size design. Figure 12 A schematic diagram of a projection imaging system architecture is provided, which combines a transmissive phase modulator and an active microdisplay to achieve projection display. Figure 12 The transmissive imaging element 320 shown is specifically a transmissive phase modulator, which can output a phase modulation signal through the phase modulation control terminal to load an arbitrary phase distribution to simulate different lens surface types.

[0131] (2) Figures 13 to 16 As shown, in Figure 3 Based on the projection imaging system including an active display, a schematic diagram of a projection imaging system architecture combining a reflective imaging element and an active microdisplay is provided. After the pre-distorted image is displayed on the display 310, the imaging element 320 can project and magnify the image displayed on the display 310 through reflection. The reflective imaging element includes: a monolithic diffractive mirror, a monolithic optical mirror, a reflective metalens, a reflective phase modulator, etc., and the reflective imaging element 320 is positioned at a certain angle to the display 310.

[0132] Figure 13 A schematic diagram of a projection imaging system architecture is provided, which combines a monolithic diffractive mirror and an active microdisplay to achieve projection display. Figure 13 The reflective imaging element 320 shown is specifically a monolithic diffractive mirror. Figure 14 A schematic diagram of a projection imaging system architecture is provided, which combines a single optical mirror (focusable) and an active microdisplay to achieve projection display. Figure 14 The transmissive imaging element 320 shown is specifically a single optical mirror, which can be any of the following: spherical mirror, aspherical mirror, freeform mirror, etc. Figure 15 A schematic diagram of a projection imaging system architecture that combines a reflective metalens and an active microdisplay to achieve projection display is provided. Figure 15 The reflective imaging element 320 shown is specifically a reflective metalens. Figure 16 A schematic diagram of a projection imaging system architecture that combines a reflective phase modulator and an active microdisplay to achieve projection display is provided. Figure 16 The reflective imaging element 320 shown is specifically a reflective phase modulator, which can output a phase modulation signal through the phase modulation control terminal to load an arbitrary phase distribution to simulate different mirror surface shapes.

[0133] (3) Figures 17 to 20 As shown, in Figure 7Based on the projection imaging system including a passive display, a schematic diagram of a projection imaging system architecture combining a transmissive imaging element and a passive microdisplay is provided. The passive microdisplay (such as...) Figures 17 to 20 The display 420 shown can be paired with a tri-color illumination source 410 (such as...). Figures 17 to 20 The laser array (LD Array) shown), the first optical path adjustment element 450 (such as... Figures 17 to 20 The reflector M1 shown), the second optical path adjustment element 460 (as shown) Figures 17 to 20 The total internal reflection (TIR) ​​lens shown is used. After the image of the pre-distorted image is displayed on the display 420, the imaging element 430 can project and magnify the image displayed on the display 420 through transmission. Transmission-type imaging elements include: monolithic diffractive lenses, monolithic optical lenses, transmission-type metalenses, transmission-type phase modulators, etc.

[0134] Figure 17 A schematic diagram of a projection imaging system architecture that combines a monolithic diffractive lens and a passive microdisplay to achieve projection display is provided. Figure 17 The transmissive imaging element 430 shown is specifically a monolithic diffractive lens. Figure 18 A schematic diagram of a projection imaging system architecture is provided, which combines a monolithic optical lens and a passive microdisplay to achieve projection display. Figure 18 The transmissive imaging element 430 shown is specifically a single optical lens, which can be any of the following: spherical lens, aspherical lens, freeform lens, etc. Figure 19 A schematic diagram of a projection imaging system architecture that combines a transmissive metalens and a passive microdisplay to achieve projection display is provided. Figure 19 The transmissive imaging element 430 shown is specifically a transmissive metalens. Figure 20 A schematic diagram of a projection imaging system architecture is provided, which combines a transmissive phase modulator and a passive microdisplay to achieve projection display. Figure 20 The transmissive imaging element 430 shown is specifically a transmissive phase modulator, which can output a phase modulation signal through the phase modulation control terminal to load an arbitrary phase distribution to simulate different lens surface types.

[0135] (4) Figures 21 to 24 As shown, in Figure 7 Based on the projection imaging system including a passive display, a schematic diagram of a projection imaging system architecture combining a reflective imaging element and a passive microdisplay is provided. The passive microdisplay (such as...) Figures 17 to 20 The display 420 shown can be paired with a tri-color illumination source 410 (such as...). Figures 17 to 20 The laser array (LD Array) shown), the first optical path adjustment element 450 (such as... Figures 17 to 20The reflector M1 shown), the second optical path adjustment element 460 (as shown) Figures 17 to 20 The total internal reflection (TIR) ​​lens shown is used. After the pre-distorted image is displayed on the display 420, the imaging element 430 can project and magnify the image displayed on the display 420 through reflection. The reflective imaging element includes: a monolithic diffractive mirror, a monolithic optical mirror, a reflective metalens, a reflective phase modulator, etc., and the reflective imaging element 430 is set at a certain angle to the display 420.

[0136] Figure 21 A schematic diagram of a projection imaging system architecture is provided, which combines a monolithic diffractive mirror and a passive microdisplay to achieve projection display. Figure 21 The reflective imaging element 430 shown is specifically a monolithic diffractive mirror. Figure 22 A schematic diagram of a projection imaging system architecture is provided, which combines a monolithic optical mirror and a passive microdisplay to achieve projection display. Figure 22 The reflective imaging element 430 shown is specifically a single optical mirror, which can be any of the following: spherical mirror, aspherical mirror, freeform mirror, etc. Figure 23 A schematic diagram of a projection imaging system architecture that combines a reflective metalens and a passive microdisplay to achieve projection display is provided. Figure 23 The reflective imaging element 430 shown is specifically a reflective metalens. Figure 24 A schematic diagram of a projection imaging system architecture that combines a reflective phase modulator and a passive microdisplay to achieve projection display is provided. Figure 24 The reflective imaging element 430 shown is specifically a reflective phase modulator, which can output a phase modulation signal through the phase modulation control terminal to load an arbitrary phase distribution to simulate different mirror surface shapes.

[0137] Based on the same inventive concept, this application also provides a projection imaging method applied to the projection imaging system described above. The solution provided by this method is similar to the solution described in the projection imaging system embodiments above. Therefore, the specific limitations in one or more projection imaging method embodiments provided below can be found in the limitations of the projection imaging system described above, and will not be repeated here.

[0138] In some embodiments, this application also provides a projection imaging method, applied to, for example... Figure 3 The projection imaging system shown.

[0139] In this embodiment, such as Figure 25 As shown, the projection imaging method includes the following steps:

[0140] Step S2502: Perform image processing on the image signal of the image to be projected, and output the processed image signal to the display; the image processing is used to: make the image output by the display be projected by the imaging element to form an enlarged image to be projected;

[0141] Step S2504: Receive the processed image signal through the display and output the image screen;

[0142] Step S2506: Receive the image through the imaging element and project and magnify the image.

[0143] In some embodiments, this application also provides another projection imaging method, applied to, for example... Figure 4 The projection imaging system shown. In this embodiment, as... Figure 26 As shown, the projection imaging method includes the following steps:

[0144] Step S2602: Perform image processing on the image signal of the image to be projected, and output the processed image signal to the display; the image processing is used to: make the image output by the display be projected by the imaging element to form an enlarged image to be projected;

[0145] Step S2604: Illumination beams are emitted through a three-color illumination source, the illumination beams and processed image signals are received through a display, and the image is output.

[0146] Step S2606: Receive the image through the imaging element and project and magnify the image.

[0147] The above technical solution has the following advantages or beneficial effects: (e.g., using...) Figure 25 Or such as Figure 26 The projection imaging method shown can process the image to be projected through the controller, ensuring that after the display receives the processed image signal, the image output by the display is projected and magnified by the imaging element to form the magnified image to be projected. This is different from the traditional projection imaging system, which relies on a complex projection lens. This simplifies the structure of the projection imaging system and is conducive to the miniaturization and integration of the projection imaging system.

[0148] In some embodiments, image processing of the image signal of the projected image includes: obtaining the target point spread function of the imaging element and the target projection ratio set for the projection imaging system; determining target pre-distortion processing parameters based on the target point spread function and the target projection ratio, and using the target pre-distortion processing parameters to update the pre-distortion processing parameters of the pre-distortion processing model to obtain the updated pre-distortion processing model; and performing image processing on the image signal of the projected image using the updated pre-distortion processing model to obtain the processed image signal.

[0149] In some embodiments, the controller includes: a first processor configured to determine target predistortion processing parameters based on the target point spread function and the target projection ratio, and to update the predistortion processing parameters of the predistortion processing model using the target predistortion processing parameters; and a second processor configured to perform image processing on the image signal of the image to be projected using the updated predistortion processing model to obtain the processed image signal.

[0150] In some embodiments, obtaining the target point spread function of the imaging element includes: obtaining the target element parameters of the imaging element; and searching for a point spread function that matches the target element parameters in the mapping relationship between the element parameters and the point spread function to obtain the target point spread function of the imaging element.

[0151] In some embodiments, obtaining the target projection ratio set for the projection imaging system includes: receiving a projection ratio setting instruction; and obtaining the target projection ratio set for the projection imaging system from the projection ratio setting instruction.

[0152] In some embodiments, determining the target predistortion processing parameters based on the target point spread function and the target projection ratio includes: determining multiple candidate predistortion processing parameters carried in the predistortion processing model; each candidate predistortion processing parameter has its own matching point spread function and projection ratio; if among the multiple candidate predistortion processing parameters, there exists a predistortion processing parameter that matches both the target point spread function and the target projection ratio, the predistortion processing parameter that matches both is used as the target predistortion processing parameter. If among the multiple candidate predistortion processing parameters, there is no predistortion processing parameter that matches both the target point spread function and the target projection ratio, multiple initial predistortion processing parameters that match the target point spread function are selected from the multiple candidate predistortion processing parameters; based on the projection ratio matched by each initial predistortion processing parameter, the target predistortion processing parameter that matches both the target point spread function and the target projection ratio is predicted.

[0153] In some embodiments, the training process of the pre-distortion processing model includes: acquiring datasets collected for multiple projection imaging test systems, the datasets including: the original input image, the expected projection images matched by the original input image at different projection ratios, and the point spread function of the imaging element in the respective projection imaging test system; for each projection imaging test system, based on the dataset of the projection imaging test system, training an initial model to calculate the deconvolution result between the expected projection image and the point spread function, and calculating the pre-distortion processing parameters between the deconvolution result and the matched original input image; and obtaining the pre-distortion processing model when the pre-distortion processing parameters corresponding to each projection imaging test system satisfy the stop calculation condition.

[0154] It should be noted that when a light beam passes through an imaging element, it is equivalent to the beam undergoing convolution processing of the imaging element's point spread function, while deconvolution is the reverse process. Deconvolution is a method used to reverse the convolution process and is often used in imaging science to remove image blur. However, directly performing mathematical deconvolution calculations usually faces problems such as numerical stability, non-uniqueness of solutions, noise amplification, pattern repetition, blurring effects, and difficulties in boundary handling. Therefore, in this embodiment, a neural network model is trained to perform deconvolution calculations to ensure the accuracy of the deconvolution calculation results. The initial model in this embodiment can be a U-net neural network (a special form of convolutional neural network). The U-net neural network consists of a symmetrical encoder and decoder, with skip connections between the encoder and decoder. The encoder consists of multiple convolutional layers, each followed by a max-pooling layer to reduce spatial dimensions and extract features. The decoder uses upsampling layers instead of max-pooling layers to restore spatial dimensions. The skip connections between the encoder and decoder allow direct feature transfer from the encoder to the corresponding decoder layer, helping to preserve positional information and reduce information loss. Using the U-net neural network can significantly improve the efficiency and accuracy of deconvolution calculation. Combined with the training of the neural network model to perform deconvolution calculation in this embodiment, the accuracy of the obtained deconvolution results can be further ensured, thereby ensuring that the pre-distortion processing parameters under each scenario can be accurately calculated.

[0155] Specifically, the model training process can be executed by a high-performance controller or by an external server or terminal. First, datasets collected from multiple projection imaging test systems can be acquired. These test systems may include displays and imaging elements, but no pre-distortion processing model has been configured yet. The point spread function of the imaging elements in each test system is known information. The dataset for each test system includes: multiple original input images, the desired projected images matched to each original input image at different projection ratios, and the point spread function of the imaging elements in the respective test system. This ensures that pre-distortion processing parameters can be trained for multiple projection ratios for each commonly used imaging element (i.e., a commonly used point spread function).

[0156] Furthermore, training can be conducted separately for each projection imaging test system (each projection imaging test system has one imaging element, i.e., corresponding to one point spread function), that is, training can be conducted separately for each point spread function condition. Specifically, based on the dataset of the imaging test system, the initial model is trained iteratively to calculate the deconvolution result between the expected projected image and the point spread function under each projection ratio, and to calculate the pre-distortion processing parameters between the deconvolution result and the matched original input image, until the pre-distortion processing parameters calculated by the model for each point spread function under each projection ratio tend to stabilize (the loss function value tends to approach the loss function threshold). At this point, it is determined that the pre-distortion processing parameters corresponding to each projection imaging test system meet the stopping calculation requirement, thus obtaining the pre-distortion processing model. The pre-distortion processing model includes the pre-distortion processing parameters corresponding to each projection ratio under each point spread function scenario.

[0157] The above technical solution has the following advantages or beneficial effects: It can perform deconvolution calculation by training a neural network model, and solve the pre-distortion processing parameters between the deconvolution result and the matched original input image. This allows the final pre-distortion processing model to learn how to accurately calculate the pre-distortion processing parameters when the point spread function and projection ratio are known. This allows the calculated pre-distortion processing parameters to process the image to be projected into the required deconvolution result (i.e., the pre-distorted image). This ensures that the processed deconvolution result, after being displayed on the monitor and then projected by the imaging element (convolved by the point spread function), can form the required projected image. Based on this, a pre-distortion processing model can be obtained. The pre-distortion processing model carries the pre-distortion processing parameters corresponding to each projection ratio under each point spread function scenario. This ensures that in subsequent applications, after the pre-distortion processing model is deployed in the projection imaging system, by flexibly updating the pre-distortion processing parameters of the pre-distortion processing model, the pre-distortion processing model can process the image to be projected in the projection imaging system into an adapted pre-distortion processed image. This ensures that the pre-distortion processed image, after being displayed on the monitor and then projected by the imaging element, can form a clear image under the specified projection ratio.

[0158] In some embodiments, acquiring datasets collected for multiple projection imaging test systems includes: for each projection imaging test system, acquiring the point spread function of the imaging element in the projection imaging test system, the original input image of the projection imaging test system, and the original projection images matched by each original input image output by the projection imaging test system at different projection ratios; performing image preprocessing on the original projection images matched by each original input image at different projection ratios to obtain the expected projection images matched by each original input image at different projection ratios; and constructing the dataset of the projection imaging test system based on the point spread function corresponding to the projection imaging test system, the original input image, and the expected projection images matched by the original input image.

[0159] Specifically, the projection imaging test system includes a display and an imaging element, but no pre-distortion processing model has been configured. Therefore, during model training, after inputting the original input image into the projection imaging test system, the resulting image is generally unclear. Image preprocessing is required to obtain the desired projection image suitable for model learning, and the image quality of the desired projection image affects the model training effect. Based on this, for each projection imaging test system, after obtaining the point spread function of the imaging element, the original input image of the projection imaging test system, and the original projection images matched by each original input image at different projection ratios, image preprocessing is performed on these matched original projection images to obtain the desired projection images matched by each original input image at different projection ratios. Thus, based on the point spread function of the projection imaging test system, the original input image, and the desired projection images matched by the original input image, a dataset for the projection imaging test system is constructed.

[0160] For example, the original projected image can be preprocessed using the following process to ensure the desired projected image conforms to the instructions: First, a large number of original projected images are read in batches, and noise is removed using denoising algorithms (such as bilateral filtering, Gaussian filtering, etc.). Then, geometric correction is performed on the original projected images to eliminate image distortion caused by factors such as camera angle and lens distortion. Color correction algorithms are then used to adjust the image's color balance, contrast, and brightness. For scenarios requiring comparison with the real projection effect, image registration techniques can be used to align the adjusted original projected image with a standard template image, ensuring geometric consistency between the images. Finally, the images that have undergone the above processing can be quality checked to ensure that their sharpness, contrast, and color meet the standards. Images that pass the quality check are used as the desired projected image. It should be noted that the above image preprocessing process can be designed as an automated image preprocessing program to improve the efficiency of dataset construction during model training. Furthermore, during the setup of the image preprocessing program, cross-validation methods can be used to evaluate the effects of different combinations of image preprocessing parameters and select the optimal parameters. A feedback mechanism can also be established to adjust poorly performing image preprocessing parameters in a timely manner. In the later stages, the preprocessing results can be checked periodically to ensure that the quality of image preprocessing meets the requirements, providing sufficient high-quality data support for model training.

[0161] The above technical solution has the following advantages or beneficial effects: It can collect the original projection images corresponding to different projection ratios under each point spread function scenario, process the original projection images into high-quality expected projection images, and then construct a dataset. This is beneficial for subsequent training of a pre-distortion processing model that can accurately and efficiently achieve adjustable projection ratios based on the dataset. This enables the projection imaging system with the pre-distortion processing model to efficiently adjust the projection display effect and ensure projection quality.

[0162] In some embodiments, based on the dataset of the projection imaging test system, an initial model is trained to calculate the deconvolution result between the desired projected image and the point spread function, and to calculate the pre-distortion processing parameters between the deconvolution result and the matched original input image. This includes: treating the matched original input image and the desired projected image in the dataset of the projection imaging test system as image groups; for each image group, using the initial model, calculating the deconvolution result between the desired projected image in the image group and the point spread function of the projection imaging test system, and calculating the pre-distortion processing parameters between the obtained deconvolution result and the original input image in the image group to obtain initial pre-distortion processing parameters; calculating the loss function value of the initial model based on the initial pre-distortion processing parameters calculated for different image groups, adjusting the model parameters of the initial model based on the loss function value until the obtained loss function value reaches the loss function threshold, stopping the calculation, and obtaining the pre-distortion processing parameters corresponding to the projection imaging test system.

[0163] Optionally, during model training, for each projection imaging test system, the original input image and the desired projection image matched in the dataset of the projection imaging test system can be treated as separate image groups for model learning. Further, for each image group, the deconvolution result between the desired projection image in the image group and the point spread function of the projection imaging test system can be calculated using the initial model. The pre-distortion processing parameters between the obtained deconvolution result and the original input image in the image group are then calculated to obtain the initial pre-distortion processing parameters. Furthermore, considering that deconvolution operations are prone to generating multiple solutions and that image noise is amplified during deconvolution, to mitigate the errors caused by deconvolution, the loss function value of the initial model can be calculated based on the initial pre-distortion processing parameters calculated for different image groups. This allows for the adjustment of the initial model parameters based on the loss function value, i.e., continuously optimizing the pre-distortion processing parameters calculated by the model for each projection ratio under each point spread function scenario. Finally, the calculation stops when the obtained loss function value reaches the loss function threshold, yielding the pre-distortion processing parameters corresponding to the projection imaging test system. It's important to note that when choosing a loss function, one can consider mean squared error (MSE), Dice coefficient loss, Jaccard exponential loss, etc. In practical applications, combining these loss functions can improve model training performance. During the adjustment of model parameters based on the loss function value, the choice of learning rate is crucial. Too high a rate can lead to unstable training, while too low a rate will make training too slow. Therefore, a learning rate decay strategy can be used to dynamically adjust the learning rate to ensure effective model training. Furthermore, the size of each batch of training data can be appropriately configured to ensure effective model training.

[0164] For example, taking a certain test device as an example, if the dataset includes: point spread function A, original input image x1, expected projection image x1' of original input image x1 at projection ratio r, original input image x2, expected projection image x2' of original input image x2 at projection ratio r, original input image x3, and expected projection image x3' of original input image x3 at projection ratio r. Based on this, the deconvolution result (x1' / A) of x1' and A can be calculated using an initial model, and the pre-distortion parameter theta1 between the deconvolution result (x1' / A) and the matched original input image x1 can be calculated, where " / " indicates deconvolution calculation. Similarly, the pre-distortion parameter theta2 can be calculated using the model based on the original input image x2, point spread function A, and expected projection image x2'; and the pre-distortion parameter theta3 can be calculated based on the original input image x3, point spread function A, and expected projection image x3'. Furthermore, by calculating the differences between theta1, theta2, and theta3, the loss function value of the model for the scenario with point spread function A and projection ratio r can be calculated. Based on the loss function value, the model parameters are optimized until the pre-distortion processing parameters calculated by the model for this scenario tend to stabilize, that is, the loss function value drops to the loss function threshold. Once the pre-distortion processing parameters corresponding to different projection ratios for each point spread function are determined, the calculation stops, and the pre-distortion processing model is obtained.

[0165] The above technical solution has the following advantages or beneficial effects: Utilizing the characteristic that neural network models can accurately perform deconvolution calculations, the model iteratively calculates the pre-distortion processing parameters between the deconvolution result and the original input image under different projection ratios for each point spread function scenario, until the model accurately obtains the pre-distortion processing parameters corresponding to different projection ratios for each point spread scenario, thus obtaining a pre-distortion processing model suitable for various scenarios. Based on this, in subsequent applications, the pre-distortion processing parameters of the pre-distortion processing model can be flexibly and quickly updated according to the target point spread function of the imaging element in the projection imaging system and the set target projection ratio. This allows for efficient adjustment of the projection display effect through the updated pre-distortion processing model, while ensuring the quality of the projected image.

[0166] In some embodiments, obtaining a pre-distortion processing model when the pre-distortion processing parameters corresponding to each projection imaging test system meet the stop calculation requirement includes: obtaining an initial pre-distortion processing model when the pre-distortion processing parameters corresponding to each projection imaging test system meet the stop calculation requirement; obtaining an image post-processing network; fusing the image post-processing network with the initial pre-distortion processing model to obtain a pre-distortion processing model; and using the output of the initial pre-distortion processing model as the input of the image post-processing network.

[0167] Specifically, to further improve the image quality of the pre-distortion processed image output by the pre-distortion processing model, if the pre-distortion processing parameters corresponding to different projection ratios for each point diffusion scenario have been accurately obtained during model training, an initial pre-distortion processing model can be obtained first. Then, an image post-processing network is acquired and fused with the initial pre-distortion processing model; that is, the output of the initial pre-distortion processing model is used as the input to the image post-processing network to obtain the final pre-distortion processing model. The image post-processing network can also be trained based on a neural network, which can enhance image contrast and adjust image color balance without affecting the original image quality.

[0168] The above technical solution has the following advantages or beneficial effects: After training the initial pre-distortion processing model, the image quality of the pre-distortion processed image output by the pre-distortion processing model can be further improved by fusing the image post-processing network with the initial pre-distortion processing model, thereby improving the projection display effect of the projection imaging system.

[0169] It's important to note that in actual model training, to comprehensively evaluate the trained model, the constructed dataset can be split, such as into training, validation, and test sets. The training set is used to train the model, the validation set is used to monitor performance and adjust hyperparameters during training, and the test set is used to ultimately evaluate the model's generalization ability. Performance metrics can include mean squared error (MSE), structural similarity index (SSIM), peak signal-to-noise ratio (PSNR), Dice coefficient or Jaccard index, and perceptual loss, to comprehensively evaluate the model's image processing quality. During training, the model's performance can be periodically evaluated on the validation set, and early stopping strategies can be used to prevent overfitting. Finally, after model training is complete, a comprehensive evaluation can be performed using a test set that was never used in the training process to ensure the model performs well on unknown data. Furthermore, the quantitative and qualitative evaluation results can be combined to analyze the model's strengths and weaknesses in different scenarios, and the model architecture or training strategy can be adjusted based on the evaluation results to improve the model's generalization ability.

[0170] In some embodiments, another projection imaging method is also provided, which can be applied to projection imaging systems that do not include imaging elements. Specifically, the original input image and the desired output image can be collected to construct a dataset. Using this dataset, a neural network model can be trained to learn how to transform the image to be projected into the desired high-quality image. Subsequently, the trained model can be deployed at the input end of the projection imaging system to process the image input to the projection imaging system, enabling the projection imaging system to display the required high-quality image.

[0171] Based on the same inventive concept, this application also provides a projection imaging apparatus for implementing the projection imaging method described above. The solution provided by this apparatus is similar to the implementation described in the above method; therefore, the specific limitations in one or more projection imaging apparatus embodiments provided below can be found in the limitations of the projection imaging method described above, and will not be repeated here.

[0172] In some embodiments, a projection imaging device is also provided, applied to, for example... Figure 3 The projection imaging system shown above includes the following devices:

[0173] The image signal processing module is used to process the image signal of the image to be projected and output the processed image signal to the display. The image processing is used to: make the image output by the display be projected by the imaging element to form an enlarged image to be projected.

[0174] The image output module is used to receive the processed image signal through the display and output the image.

[0175] The image projection module is used to receive images through the imaging element and project and magnify the images.

[0176] In some embodiments, a projection imaging device is also provided, applied to, for example... Figure 4 The projection imaging system shown above includes the following devices:

[0177] The image signal processing module is used to process the image signal of the image to be projected and output the processed image signal to the display. The image processing is used to: make the image output by the display be projected by the imaging element to form an enlarged image to be projected.

[0178] The image output module is used to emit an illumination beam through a three-color illumination source, receive the illumination beam and the processed image signal through a display, and output the image.

[0179] The image projection module is used to receive images through the imaging element and project and magnify the images.

[0180] The aforementioned projection imaging device can process the image to be projected through a controller, ensuring that after the display receives the processed image signal, the image output by the display is projected and magnified by the imaging element to form the magnified image to be projected. This is unlike traditional projection imaging systems that rely on complex projection lenses, simplifying the structure of the projection imaging system and facilitating its miniaturization and integration. In some embodiments, the image signal processing module further includes: a configuration acquisition unit for acquiring the target point spread function of the imaging element and the target projection ratio set for the projection imaging system; a model update unit for determining the target pre-distortion processing parameters based on the target point spread function and the target projection ratio, and updating the pre-distortion processing parameters of the pre-distortion processing model using the target pre-distortion processing parameters to obtain the updated pre-distortion processing model; and an image processing unit for performing image processing on the image signal of the image to be projected using the updated pre-distortion processing model to obtain the processed image signal.

[0181] In some embodiments, the controller includes: a first processor configured to determine target predistortion processing parameters based on the target point spread function and the target projection ratio, and to update the predistortion processing parameters of the predistortion processing model using the target predistortion processing parameters; and a second processor configured to perform image processing on the image signal of the image to be projected using the updated predistortion processing model to obtain the processed image signal.

[0182] In some embodiments, the configuration acquisition unit is specifically used to: acquire target element parameters of the imaging element; and search for a point spread function that matches the target element parameters in the mapping relationship between element parameters and point spread functions to obtain the target point spread function of the imaging element. The configuration acquisition unit is also used to: receive a projection ratio setting instruction; and acquire the target projection ratio set for the projection imaging system from the projection ratio setting instruction.

[0183] In some embodiments, the model update unit is specifically used to: determine multiple candidate predistortion processing parameters carried in the predistortion processing model; each candidate predistortion processing parameter has its own matching point spread function and projection ratio; if among the multiple candidate predistortion processing parameters, there exists a predistortion processing parameter that matches both the target point spread function and the target projection ratio, the predistortion processing parameter that matches both is used as the target predistortion processing parameter. If among the multiple candidate predistortion processing parameters, there is no predistortion processing parameter that matches both the target point spread function and the target projection ratio, multiple initial predistortion processing parameters that match the target point spread function are selected from the multiple candidate predistortion processing parameters; based on the projection ratio matched by each initial predistortion processing parameter, the target predistortion processing parameter that matches both the target point spread function and the target projection ratio is predicted.

[0184] In some embodiments, the above-described projection imaging device further includes a model training module, which includes: a dataset acquisition unit, used to acquire datasets collected for multiple projection imaging test systems respectively, the datasets including: original input images, expected projection images matched by the original input images at different projection ratios, and point spread functions of imaging elements in the respective projection imaging test systems; a computational training unit, used for each projection imaging test system, based on the dataset of the projection imaging test system, to train an initial model to calculate the deconvolution result between the expected projection image and the point spread function, and to calculate the pre-distortion processing parameters between the deconvolution result and the matched original input image; and a model acquisition unit, used to obtain a pre-distortion processing model when the pre-distortion processing parameters corresponding to each projection imaging test system meet the condition of stopping computation.

[0185] In some embodiments, the dataset acquisition unit is specifically used to: for each projection imaging test system, acquire the point spread function of the imaging element in the projection imaging test system, the original input image of the projection imaging test system, and the original projection images matched by each original input image output by the projection imaging test system at different projection ratios; perform image preprocessing on the original projection images matched by each original input image at different projection ratios to obtain the expected projection images matched by each original input image at different projection ratios; and construct the dataset of the projection imaging test system based on the point spread function corresponding to the projection imaging test system, the original input image, and the expected projection images matched by the original input image.

[0186] In some embodiments, the computational training unit is specifically used to: treat the original input image and the desired projection image matched in the dataset of the projection imaging test system as an image group; for each image group, using an initial model, calculate the deconvolution result between the desired projection image in the image group and the point spread function of the projection imaging test system, and calculate the pre-distortion processing parameters between the obtained deconvolution result and the original input image in the image group to obtain the initial pre-distortion processing parameters; calculate the loss function value of the initial model based on the initial pre-distortion processing parameters calculated for different image groups, adjust the model parameters of the initial model based on the loss function value, until the obtained loss function value reaches the loss function threshold, stop the calculation, and obtain the pre-distortion processing parameters corresponding to the projection imaging test system.

[0187] In some embodiments, the model acquisition unit is specifically used to: obtain an initial pre-distortion processing model when the pre-distortion processing parameters corresponding to each projection imaging test system meet the stop calculation condition; acquire an image post-processing network, fuse the image post-processing network with the initial pre-distortion processing model to obtain a pre-distortion processing model; and use the output of the initial pre-distortion processing model as the input of the image post-processing network.

[0188] Each module in the aforementioned projection imaging device can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device, or stored in the memory of a computer device as software, so that the processor can call and execute the operations corresponding to each module.

[0189] In some embodiments, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the above-described projection imaging method.

[0190] In some embodiments, a computer program product is provided, including a computer program that, when executed by a processor, implements the above-described projection imaging method.

[0191] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments of the above methods. Any references to memory, databases, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided in this application may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided in this application may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, quantum computing-based data processing logic devices, etc., and are not limited to these.

[0192] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0193] The above embodiments are merely illustrative of several implementation methods of this application, and their descriptions are relatively specific and detailed. However, they should not be construed as limiting the scope of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this application should be determined by the appended claims.

Claims

1. A projection imaging system, characterized in that, The projection imaging system includes: The display is configured to receive image signals and output image frames; An imaging element is configured to receive the image and project and magnify the image. The controller is configured to perform image processing on the image signal of the image to be projected and output the processed image signal to the display; the image processing is used to: make the image output by the display be projected by the imaging element to form an enlarged image of the image to be projected.

2. A projection imaging system, characterized in that, The projection imaging system includes: The tri-color illumination source is configured to emit an illumination beam; The display is configured to receive image signals and the illumination beam, and to output an image. An imaging element is configured to receive the image and project and magnify the image. The controller is configured to perform image processing on the image signal of the image to be projected and output the processed image signal to the display; the image processing is used to: make the image output by the display be projected by the imaging element to form an enlarged image of the image to be projected.

3. The projection imaging system according to claim 2, characterized in that, The projection imaging system includes: A first optical path adjustment element is configured to cause the display to receive the illumination beam by adjusting the projection optical path of the illumination beam.

4. The projection imaging system according to claim 2, characterized in that, The projection imaging system includes: The second optical path adjustment element is configured to adjust the projection optical path of the image frame so that the imaging element receives the image frame.

5. The projection imaging system according to any one of claims 1 to 4, characterized in that, When the controller performs the step of image processing on the image signal of the image to be projected, it is further configured to: Obtain the target point spread function of the imaging element and the target projection ratio set for the projection imaging system; Based on the target point spread function and the target projection ratio, the target pre-distortion processing parameters are determined, and the pre-distortion processing parameters of the pre-distortion processing model are updated using the target pre-distortion processing parameters to obtain the updated pre-distortion processing model; The updated pre-distortion processing model is used to process the image signal of the image to be projected, thereby obtaining the processed image signal.

6. The projection imaging system according to claim 5, characterized in that, The controller includes: A first processor is configured to determine the target predistortion processing parameters based on the target point spread function and the target projection ratio, and to update the predistortion processing parameters of the predistortion processing model using the target predistortion processing parameters. The second processor is configured to perform image processing on the image signal of the image to be projected using the updated pre-distortion processing model to obtain the processed image signal.

7. The projection imaging system according to claim 5, characterized in that, When the controller performs the step of acquiring the target point spread function of the imaging element, it is further configured to: Obtain the target element parameters of the imaging element; In the mapping relationship between element parameters and point spread functions, a point spread function that matches the target element parameters is found to obtain the target point spread function of the imaging element.

8. The projection imaging system according to claim 5, characterized in that, When the controller performs the step of obtaining the target projection ratio set for the projection imaging system, it is further configured to: Receive projection ratio setting instructions; The target projection ratio set for the projection imaging system is obtained from the projection ratio setting instruction.

9. The projection imaging system according to claim 5, characterized in that, When the controller performs the step of determining the target pre-distortion processing parameters based on the target point spread function and the target projection ratio, it is further configured to: The predistortion processing model is used to determine a variety of candidate predistortion processing parameters; each candidate predistortion processing parameter has its own matching point spread function and projection ratio. If among the multiple candidate predistortion processing parameters, there exists a predistortion processing parameter that matches both the target point spread function and the target projection ratio, then the matching predistortion processing parameter shall be used as the target predistortion processing parameter.

10. The projection imaging system according to claim 5, characterized in that, When the controller performs the step of determining the target pre-distortion processing parameters based on the target point spread function and the target projection ratio, it is further configured to: If none of the candidate predistortion processing parameters carried by the predistortion processing model match both the target point spread function and the target projection ratio, then multiple initial predistortion processing parameters that match the target point spread function are selected from the multiple candidate predistortion processing parameters. Based on the projection ratio matched by each of the initial pre-distortion processing parameters, predict the target pre-distortion processing parameters that match both the target point spread function and the target projection ratio.

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