A spectral test system and spectral test method for display screen sub-pixels

Abstract

The application discloses a spectrum testing system and method for sub-pixels of a display screen, which is used for performing spectrum testing on the sub-pixels of the display screen and meets the demand of optical performance testing. The method comprises the following steps: a high-sensitivity camera, a hyperspectral instrument, a processing device, a first light splitting element and a microscope objective are used; the microscope objective is aligned with the surface of the display screen and is used for optically magnifying the sub-pixel area of the display screen; the first light splitting element is located at the light path output end of the microscope objective and divides the magnified light signal into a first light path and a second light path; the first light path is input into the hyperspectral instrument, the hyperspectral instrument is used for dispersing and splitting the light in the first light path and recording spectrum data; the second light path is input into the high-sensitivity camera, the high-sensitivity camera is used for acquiring the image of the sub-pixel area; the processing device is connected with the hyperspectral instrument and the high-sensitivity camera respectively, and the processing device is used for generating a hyperspectral data cube containing the spectrum of a single sub-pixel according to the spectrum data and the image.

Description

Technical Field

[0001] This application relates to the field of display screen testing equipment technology, and in particular to a spectral testing system and method for display screen sub-pixels. Background Technology

[0002] In the manufacturing process of display screens (such as LCD, OLED, MicroLED), comprehensive and accurate optical performance testing is required to ensure the display quality of the display screen.

[0003] In traditional testing methods, a commonly used testing device is the single-point spectrophotometer. Its working principle is to use an aperture with a finite size (usually a few millimeters in diameter, such as the common 5mm aperture) to measure a specific area of ​​the display screen. After measurement, the average spectral power distribution (SPD) curve of that area can be obtained, which is used to further calculate optical parameters such as chromaticity coordinates, color temperature, and color gamut coverage, providing an important basis for evaluating the overall performance of the display screen.

[0004] Currently, mainstream display screens are composed of red (R), green (G), and blue (B) subpixels. The size of these subpixels is typically in the micrometer range, which is orders of magnitude larger than the aperture size (5mm) of a single-point spectrophotometer. This means that when using a single-point spectrophotometer for measurement, the area covered by its aperture contains a large number of R, G, and B subpixels, and the measurement result is actually the white light spectrum formed by the mixed emission of these subpixels.

[0005] The spectral characteristics of a single subpixel have a direct and significant impact on key performance indicators of a display screen, such as color accuracy, contrast ratio, and brightness uniformity. Therefore, because single-point spectrophotometers cannot separate the spectrum of a single R, G, or B subpixel, their testing methods are no longer sufficient to meet the increasingly sophisticated optical performance testing requirements of modern displays. Summary of the Invention

[0006] To address the aforementioned technical problems, this application provides a spectral testing system and method for sub-pixels of a display screen, which can perform spectral testing on the sub-pixels of the display screen to meet the requirements of optical performance testing.

[0007] The technical solution provided in this application is described below:

[0008] The first aspect of this application provides a spectral testing system for sub-pixels of a display screen, comprising:

[0009] High-sensitivity camera, hyperspectrometer, processing equipment, first spectroscopic element, and microscope objective;

[0010] The microscope objective is aligned with the surface of the display screen to optically magnify the sub-pixel region of the display screen; the first beam splitter is located at the optical path output end of the microscope objective, splitting the magnified light signal into a first optical path and a second optical path; the first optical path is input to the hyperspectral analyzer, which performs dispersive spectral splitting on the first optical path and records spectral data; the second optical path is input to the high-sensitivity camera, which acquires an image of the sub-pixel region; the processing device is connected to the hyperspectral analyzer and the high-sensitivity camera respectively, and the processing device generates a hyperspectral data cube containing the spectrum of a single sub-pixel based on the spectral data and the image.

[0011] Optionally, the spectral testing system further includes a testing platform located below the microscope objective, which is used to support and fix the display screen.

[0012] Optionally, the test platform includes a fixed frame, a movable plate, and a two-dimensional drive component; the movable plate is disposed above the fixed frame, the two-dimensional drive component is disposed between the movable plate and the fixed frame, the two-dimensional drive component is signal-connected to the processing device, and the two-dimensional drive component is controlled to drive the movable plate to move at a preset step distance.

[0013] Optionally, the processing device includes a motion control module and a stitching module. The motion control module is signal-connected to the two-dimensional driving component, and the stitching module is electrically connected to the high-sensitivity camera and the hyperspectral analyzer, respectively. The stitching module is used to stitch together the images and spectral data of adjacent sub-pixel regions.

[0014] Optionally, the spectral testing system further includes a second spectroscopic element and an observation device. The second spectroscopic element is disposed in the optical path between the microscope objective and the high-sensitivity camera. The second spectroscopic element is used to split a third optical path from the optical path between the microscope objective and the high-sensitivity camera. The observation device is disposed in the third optical path.

[0015] Optionally, the observation device is a bright-field camera or a trinocular telescope.

[0016] Optionally, the hyperspectral imager has a spectroscopic range of 400-700 nm and a spectral resolution of ≤5 nm; the high-sensitivity camera has a quantum efficiency of >80%.

[0017] The second aspect of this application provides a spectral testing method for sub-pixels of a display screen, applied to the spectral testing system described in any one of the first aspects, comprising:

[0018] S1. In a dark room measurement environment, the display screen is lit up. The light signal on the display screen is optically amplified by the microscope objective and then split into a first optical path and a second optical path by the first beam splitter. The first optical path enters the hyperspectral analyzer and the second optical path enters the high-sensitivity camera.

[0019] S2. Synchronously adjust the working distance and aperture of the microscope objective until the high-sensitivity camera captures a clear image of the sub-pixel area of ​​the display screen;

[0020] S3. Perform dispersive spectroscopy on the first optical path using a hyperspectral analyzer and acquire spectral data of the current field of view;

[0021] S4. Image the second optical path using a high-sensitivity camera to obtain an image of the sub-pixel region corresponding to the current field of view;

[0022] S5. Based on the spectral data and the image, the processing device generates a hyperspectral data cube containing the independent spectra of each sub-pixel in the current field of view.

[0023] Optionally, after step S2, the spectral testing method further includes:

[0024] S6. Based on the field of view of the microscope objective, calculate the single step distance of the test platform along the width and height of the display screen, respectively, with the display screen placed on the test platform;

[0025] S7. Control the display screen to move according to the step distance through the test platform. After each movement is completed, execute steps S3-S5 to obtain multiple hyperspectral data cubes of multiple fields of view until the entire display screen is covered; then execute step S8.

[0026] S8. The hyperspectral data cubes of all fields of view are stitched together by the processing device to generate a global sub-pixel spectral distribution map of the display screen.

[0027] Optionally, after step S8, the spectral testing method further includes:

[0028] S9. The processing device constructs an interactive visualization interface based on the global sub-pixel spectral distribution map;

[0029] S10. In response to the user clicking on the location of the interactive visualization interface, extract the sub-pixel spectral curve corresponding to the location from the global sub-pixel spectral distribution map and display it;

[0030] And / or in response to a wavelength range selected by the user in the interactive visualization interface, display the corresponding display area within the wavelength range.

[0031] Optionally, step S2 further includes:

[0032] A second beam splitter is provided in the optical path between the microscope objective and the high-sensitivity camera, and a third optical path is split from the optical path between the microscope objective and the high-sensitivity camera by the second beam splitter; an observation device is provided in the third optical path, and the third optical path enters the observation device;

[0033] The working distance and aperture of the microscope objective are adjusted by the imaging sharpness of the sub-pixels of the display screen in the observation device.

[0034] As can be seen from the above technical solutions, this application has the following beneficial effects:

[0035] This application aligns a microscope objective with the surface of a display screen, optically magnifying the sub-pixel region of the screen. A first beam splitter is positioned at the optical output of the microscope objective, splitting the amplified light signal into a first optical path and a second optical path. The first optical path is input to a hyperspectral analyzer, which performs dispersive spectral analysis and records the spectral data. The second optical path is input to a high-sensitivity camera, which acquires an image of the sub-pixel region. A processing device is connected to both the hyperspectral analyzer and the high-sensitivity camera. Based on the spectral data and the image, the processing device generates a hyperspectral data cube containing the spectrum of each individual sub-pixel. Thus, through the optical magnification of the microscope objective and the dispersive spectral analysis of the hyperspectral analyzer, the spectral characteristics of individual R, G, and B sub-pixels can be separated and measured. This solves the problem that traditional single-point spectrophotometers cannot separate the spectrum of individual sub-pixels, significantly improving the accuracy and precision of the measurement. Furthermore, the hyperspectral data cube generated by the processing device can acquire the spectral characteristics of each sub-pixel, meeting the increasingly sophisticated optical performance testing requirements of modern displays. Attached Figure Description

[0036] To more clearly illustrate the technical solutions in this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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 This is a schematic diagram of the spectral testing system for the sub-pixels of the display screen in this application;

[0038] Figure 2 This is a schematic diagram of the first beam-splitting element of this application located between the high-sensitivity camera and the second beam-splitting element;

[0039] Figure 3 This is a schematic diagram of the first beam-splitting element of this application located between the microscope objective and the second beam-splitting element;

[0040] Figure 4 This is a top view of the display screen in the spectral testing system for sub-pixels of the display screen according to this application;

[0041] Figure 5 This is a schematic diagram of the spectral testing method for the sub-pixels of the display screen in this application;

[0042] Figure 6 A schematic diagram of the method for generating a global sub-pixel spectral distribution map of the display screen according to this application;

[0043] Figure 7 A schematic diagram of the method for constructing an interactive visual interface for this application;

[0044] In the figure, there is a high-sensitivity camera 01, a hyperspectral analyzer 02, a microscope objective 03, a display screen 04, a test platform 05, a second spectrometer 06, an observation device 07, a first spectrometer 08, and a processing device 09. Detailed Implementation

[0045] In this invention, the terms "upper", "lower", "left", "right", "front", "rear", "top", "bottom", "inner", "outer", "middle", "vertical", "horizontal", "lateral", "longitudinal", etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are only used to describe the relative positional relationship between the components or parts and do not specifically limit the specific installation orientation of each component or part.

[0046] Furthermore, in addition to indicating location or positional relationship, some of the aforementioned terms may also have other meanings. For example, the term "above" may also be used in some cases to indicate a certain dependency or connection relationship. Those skilled in the art can understand the specific meaning of these terms in this application based on the specific circumstances.

[0047] Furthermore, the terms "installation," "setup," "equipped with," "connection," and "linked" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral structure; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium, or an internal connection between two devices, components, or parts. Those skilled in the art can understand the specific meaning of these terms in this application based on the specific circumstances.

[0048] Furthermore, the structures, proportions, sizes, etc., drawn in the accompanying drawings of this application are only used to complement the content disclosed in the specification for those skilled in the art to understand and read, and are not intended to limit the conditions under which this application can be implemented. Therefore, they have no substantial technical significance. Any modification to the structure, change in the proportional relationship, or adjustment of the size, without affecting the effects and purposes that this application can produce, should still fall within the scope of the technical content disclosed in this application.

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

[0050] To address the technical problem that traditional single-point spectrophotometers can only perform spectral testing on white light spectra of sub-pixel mixtures, failing to achieve sub-pixel-level spectral testing and thus unable to meet the increasingly refined optical performance testing requirements of modern displays, this application provides a spectral testing system and method for sub-pixels of a display screen, used to perform spectral testing on the sub-pixels of the display screen to meet the needs of optical performance testing. The specific implementation process of this application is described below.

[0051] Please see Figures 1 to 4 The first aspect of this application provides a spectral testing system for sub-pixels of a display screen, comprising: a high-sensitivity camera 01, a hyperspectral analyzer 02, a processing device 09, a first beam splitter 08, and a microscope objective 03; the microscope objective 03 is aligned with the surface of the display screen 04 for optical magnification of the sub-pixel region of the display screen 04; the first beam splitter 08 is located at the optical path output end of the microscope objective 03, and splits the magnified optical signal into a first optical path and a second optical path; the first optical path is input to the hyperspectral analyzer 02, which is used to perform dispersive spectral splitting on the first optical path and record spectral data; the second optical path is input to the high-sensitivity camera 01, which is used to acquire an image of the sub-pixel region; the processing device 09 is connected to the hyperspectral analyzer 02 and the high-sensitivity camera 01 respectively, and is used to generate a hyperspectral data cube containing the spectrum of a single sub-pixel based on the spectral data and the image.

[0052] The microscope objective 03 is aligned with the surface of the display screen 04. The microscope objective 03 can optically magnify a specific area of ​​the display screen 04 (the area aligned with the microscope objective 03) to the micrometer level. That is, the microscope objective 03 can observe all the sub-pixels of the specific area, making the subsequent spectral acquisition and analysis more accurate and clear.

[0053] The first beam splitter 08 is located at the optical output end of the microscope objective 03. After passing through the first beam splitter 08, the optical signal is divided into two optical paths, namely the first optical path and the second optical path. The first optical path is introduced into the hyperspectral analyzer 02, and the second optical path is introduced into the high-sensitivity camera 01.

[0054] The first beam splitter 08 includes, but is not limited to, coated beam splitting glass (reflectivity / transmittance = 50 / 50), multi-core fiber coupled beam splitter, liquid crystal adjustable beam splitter, grating, and prism.

[0055] The hyperspectral analyzer 02 receives the magnified light signal (first optical path) collected by the microscope objective 03. Before receiving the magnified light signal, the hyperspectral analyzer 02 needs to perform white balance calibration. Both the first and second optical paths produce composite light, composed of several monochromatic lights of different wavelengths. After receiving the light signal, the hyperspectral analyzer 02 uses a dispersive element (such as a prism or grating) to decompose the composite light into monochromatic lights of different wavelengths, achieving dispersive spectral separation. The different wavelengths of light are separated spatially according to certain rules after dispersion, forming a spectrum. In this way, the hyperspectral analyzer 02 can separate the light of various wavelengths emitted by the sub-pixels of the display screen 04, providing crucial data for subsequently acquiring the spectral information of the sub-pixels.

[0056] After processing the optical signal of the first optical path, the hyperspectral analyzer 02 performs spectral analysis on each sub-pixel, outputs the wavelength of each sub-pixel (including bright red, green and blue sub-pixels), and outputs a spectral curve that can be mapped to a spatial location.

[0057] The high-sensitivity camera 01 receives the second optical path after the light is split by the first beam-splitting element 08. The high-sensitivity camera 01 has high light sensitivity, capable of capturing weak light signals emitted by sub-pixels, such as grayscale values ​​(DN), ensuring the accuracy and reliability of the measurement results. The high-sensitivity camera 01 features high quantum efficiency (>80%) and low noise.

[0058] The high-sensitivity camera 01 captures images of the sub-pixel areas on the display screen 04 via a second optical path. The captured images can intuitively display information such as the shape, position, and arrangement of the sub-pixels, as well as capture weak light signals (grayscale values).

[0059] Processing device 09 integrates the data output by hyperspectrometer 02 and the image output by high-sensitivity camera 01 to generate a hyperspectral data cube containing the spectrum of a single sub-pixel.

[0060] The processing device 09 correlates the spectral data and image data acquired at the same time to ensure that the spectral information of each sub-pixel corresponds to its position in the image.

[0061] A hyperspectral data cube refers to a data structure generated through spatial-spectral registration, which includes the following dimensions: a spatial dimension (x, y) to identify the physical location of sub-pixels; a spectral dimension (λ) to identify the wavelength of visible light; and an intensity dimension (DN) to identify the gray value at the corresponding wavelength.

[0062] In this embodiment, by aligning the microscope objective 03 with the surface of the display screen 04, the sub-pixel region on the display screen 04 is optically magnified by the microscope objective 03. The first beam splitter 08 is placed at the optical path output end of the microscope objective 03, and the magnified light signal is divided into a first optical path and a second optical path by the first beam splitter 08. The first optical path is input to the hyperspectral analyzer 02, which performs dispersive spectral separation on the first optical path and records the spectral data. The second optical path is input to the high-sensitivity camera 01, which acquires the image of the sub-pixel region. The processing device 09 is connected to the hyperspectral analyzer 02 and the high-sensitivity camera 01, respectively. Thus, the processing device 09 generates a hyperspectral data cube containing the spectrum of a single sub-pixel based on the spectral data and the image. Therefore, through the optical magnification of the microscope objective 03 and the dispersive spectral separation of the hyperspectral analyzer 02, the spectral characteristics of a single R, G, B sub-pixel can be separated and measured, solving the problem that traditional single-point spectrophotometers cannot separate the spectrum of a single sub-pixel, and greatly improving the accuracy and precision of the measurement. Furthermore, by processing the hyperspectral data cube generated by device 09, the spectral characteristics of each sub-pixel can be obtained, meeting the increasingly refined requirements of modern displays for optical performance testing.

[0063] In an optional embodiment, the spectral testing system further includes a testing platform 05 located below the microscope objective 03, which is used to support and fix the display screen 04.

[0064] The test platform 05 has high stability, ensuring that the display screen 04 does not change position during the spectral test, thereby ensuring the accuracy of the test results. In actual use, the display screen 04 is first fixed on the test platform 05, and then the microscope objective 03 is aligned with a specific area of ​​the display screen 04.

[0065] Since the display screen 04 is optically magnified through the microscope objective 03, and the display screen 04 is generally large, only a portion of the area can be displayed at a time through the microscope objective 03. If spectral testing of multiple or all areas of the display screen 04 is required, the microscope objective 03, the hyperspectral analyzer 02, and the high-sensitivity camera 01 need to be moved synchronously. However, this carries the risk of movement deviation, which necessitates parameter readjustment, such as readjusting the aperture size of the microscope objective 03. Therefore, it is possible to move only the display screen 04. Specifically, a movement function is added to the test platform 05, the details of which are described below:

[0066] In this optional embodiment, the test platform 05 includes a fixed frame, a movable plate, and a two-dimensional drive component; the movable plate is disposed above the fixed frame, the two-dimensional drive component is disposed between the movable plate and the fixed frame, the two-dimensional drive component is signal-connected to the processing device, and the two-dimensional drive component is controlled to drive the movable plate to move at a preset step distance.

[0067] The mounting bracket is made of high-strength and high-stability materials, such as aluminum alloy or stainless steel, which can withstand the weight of the moving plate, display screen 04 and 2D drive components. When the 2D drive components drive the moving plate, the mounting bracket itself will not produce significant deformation or vibration, thus ensuring the stability and accuracy of the entire testing process.

[0068] The movable plate is positioned above the fixed frame and is used to directly support the display screen 04. The surface of the movable plate is treated with anti-static agents to prevent damage to the display screen 04 caused by static electricity during testing, and also to reduce the interference of static electricity on the measurement signal.

[0069] The movable plate is connected to the two-dimensional drive component through a guide rail slider mechanism or a lead screw nut mechanism, thereby ensuring that the power of the two-dimensional drive component is accurately transmitted to the movable plate and that the movable plate can move smoothly and accurately in a direction parallel to the plane of the display screen 04.

[0070] The preset step distance includes the movement distance on the width of the display screen 04 and the movement distance on the length of the display screen 04. The preset step distance is calculated from the display screen size and the current field of view size. The specific calculation process will be described in detail in the subsequent spectral testing methods.

[0071] Two-dimensional drive components can be implemented using stepper motors or servo motors in conjunction with lead screw and nut mechanisms and guide rail and slider mechanisms. For example, a set of stepper motors and lead screw and nut mechanisms can be installed in the X and Y axes respectively. By controlling the rotation of the stepper motors, the lead screw is rotated, thereby causing the nut to move on the lead screw, which in turn drives the moving plate to move in the corresponding direction.

[0072] It should be noted that the movement accuracy of the two-dimensional driving component reaches the micrometer level, which meets the requirements for precise measurement of the 04 sub-pixels of the display screen.

[0073] The processing device 09 has a control function. The processing device 09 sends a movement signal to the two-dimensional drive component, which controls the movement of the moving plate, thereby realizing the movement of the display screen 04.

[0074] In this embodiment, after the spectral test of the current field of view (the area of ​​the display screen 04 that the microscope objective 03 is currently aligned with and magnified) is completed, the moving plate is controlled to move by the two-dimensional driving component according to the test requirements. The moving position can be the adjacent field of view of the previous field of view, or the field of view corresponding to the randomly selected area of ​​the display screen 04.

[0075] In an optional embodiment, the processing device 09 is provided with a motion control module and a stitching module. The motion control module is signal-connected to the two-dimensional driving component, and the stitching module is signal-connected to the high-sensitivity camera 01 and the hyperspectral analyzer 02, respectively. The stitching module is used to stitch together the image and spectral data of adjacent sub-pixel regions.

[0076] The motion control module establishes a signal connection with the two-dimensional drive component and commands the movement of the two-dimensional drive component by sending control signals; the stitching module interacts with the high-sensitivity camera 01 and the hyperspectral instrument 02 respectively, receives the images and spectral data collected by them, and performs subsequent stitching processing.

[0077] The processing device 09 can plan the motion trajectory of the two-dimensional driving component according to the preset test requirements and the layout of the sub-pixels of the display screen, and send control signals to the two-dimensional driving component through the motion control module so that the display screen 04 moves according to the motion trajectory. For example, for a large-area display screen, it needs to move in a certain order and step size to ensure that all sub-pixel areas on the display screen 04 can be covered.

[0078] For the field of view currently being pointed at by the microscope objective 03, the hyperspectral analyzer 02 performs spectral dispersion on the light signal of the first optical path and outputs the corresponding spectral curve for each sub-pixel; at the same time, the high-sensitivity camera acquires the image of the current field of view according to the second optical path. Under the optical magnification of the microscope objective 03, the sub-pixels in the captured image are clear. Then, the processing device 09 generates a hyperspectral data cube containing the spectrum of a single sub-pixel based on the spectral data and image under the current field of view, thereby obtaining a hyperspectral data cube of a single area (current field of view) on the display screen 04.

[0079] Then, the moving control module controls the moving plate to move. The processing device 09 generates a hyperspectral data cube corresponding to each area it moves according to the requirements. It can obtain the sub-pixel spectra of multiple areas on the display screen. The multiple areas are combined to form the entire area of ​​the display screen. The hyperspectral data cubes of multiple areas are stored in the processing device 09. The processing device 09 stitches the hyperspectral data cubes of each area through the stitching module. After stitching, the sub-pixel spectral distribution map of the entire display screen is obtained. The specific stitching process will be explained in detail in the subsequent spectral testing method.

[0080] The processing equipment can be servers, computers, etc.

[0081] The above embodiments can perform sub-pixel spectral testing on the display screen 04, but cannot achieve precise positioning and focusing. Therefore, a third optical path can be added to the above embodiments to focus the microscope objective 03. The specific description of the third optical path is as follows:

[0082] Please continue reading. Figure 2 and Figure 3 In an optional embodiment, the spectral testing system further includes a second beam splitter 06 and an observation element 07. The second beam splitter 06 is disposed in the optical path between the microscope objective 03 and the high-sensitivity camera 01. The second beam splitter 06 is used to split a third optical path from the optical path between the microscope objective and the high-sensitivity camera. The observation element 07 is disposed in the third optical path.

[0083] Based on the aforementioned first beam splitter 08, a second beam splitter 06 is added. The second beam splitter 06 can be set between the high-sensitivity camera 01 and the first beam splitter 08, or it can be set between the microscope objective lens 03 and the first beam splitter 08.

[0084] The second beam splitter 06 can separate a portion of the light signal between the microscope objective 03 and the high-sensitivity camera 01 to form a third optical path, which is then introduced into the observation element 07. Specifically, if the second beam splitter 06 is positioned between the high-sensitivity camera 01 and the first beam splitter 08, such as... Figure 3 The second optical path, formed after being split by the first beam splitter 08, first enters the second beam splitter 06. The second beam splitter 06 splits a portion of the light signal on the second optical path (the third optical path) and introduces it into the observation element 07. The remaining light signal in the second optical path continues to be introduced into the high-sensitivity camera 01. If the second beam splitter 06 is placed between the microscope objective 03 and the first beam splitter 08, such as... Figure 2 The optical signal magnified by the microscope objective 03 first enters the second beam splitter 06. The second beam splitter 06 divides the optical signal into a part (the third optical path) and introduces it into the observation device 07. The remaining part of the optical signal is introduced into the first beam splitter 08. After passing through the first beam splitter 08, the first optical path and the second optical path are formed.

[0085] The second beam splitter 06 can be a cubic prism, which splits the incident light into two beams by coating a beam splitting film on the contact surface of the two prisms.

[0086] The splitting ratio of the first beam splitter 08 is 50:50, meaning the first and second optical paths each account for 50% of the incident light (the optical signal optically amplified by the microscope objective 03). The splitting ratio of the second beam splitter 06 can also be set to 50:50. There are two scenarios: when the second beam splitter 06 is positioned between the microscope objective 03 and the first beam splitter 08, the third optical path and the optical path entering the first beam splitter 08 each account for 50% of the incident light (the optical signal optically amplified by the microscope objective 03); when the second beam splitter 06 is positioned between the first beam splitter 08 and the high-sensitivity camera 01, the third optical path and the optical path entering the high-sensitivity camera 01 each account for 50% of the incident light (the second optical path formed by the splitting by the first beam splitter 08).

[0087] In this application, the splitting ratio of the second splitting element 06 and the first splitting element 08 can be set according to actual needs. For example, the splitting ratio of the second splitting element 06 can be set to 20:80, and the splitting ratio of the first splitting element 08 can be set to 40:60. The specific splitting ratio is not limited here, and the actual achievable ratio shall prevail.

[0088] In this embodiment, the observation element 07 on the third optical path is used for focusing the microscope objective 03. That is, by adjusting the microscope objective 03 until a clear sub-pixel can be observed on the observation element 07, the high-sensitivity camera 01 can also acquire a clear image corresponding to the sub-pixel. The operator can use the observation element 07 to determine whether the microscope objective 03 is accurately focused, i.e., whether a clear image of the sub-pixel is observed by the observation element 07. If it is not clear, the microscope objective 03 is adjusted.

[0089] In this optional embodiment, the observation element 07 is a bright-field camera or a trinocular lens. The specific selection of the observation element 07 is determined according to actual needs and is not specifically limited here.

[0090] In an optional embodiment, the hyperspectral instrument 02 has a spectroscopic range of 400-700nm and a spectral resolution of ≤5nm; the high-sensitivity camera has a quantum efficiency of >80%.

[0091] The spectrophotometer range refers to the range of light wavelengths that the hyperspectral analyzer 02 can detect and analyze. The display screen 04 displays various colors by mixing different proportions of the three primary colors of light: red, green, and blue. The hyperspectral analyzer 02 can accurately measure the spectral distribution of each color light within the 400-700nm range, including parameters such as peak wavelength and full width at half maximum (FWHM). By comparing with a standard color spectrum, the accuracy of the colors displayed on the display screen 04 can be evaluated, and it can be determined whether there is any color deviation or distortion. For example, if the peak wavelength of the red light displayed on the display screen 04 deviates from the wavelength range of standard red light, it indicates that the display screen 04 has a problem with color inaccuracy in displaying red.

[0092] In the test of the display 04 spectrum, the high spectral resolution can detect subtle changes in the color light spectrum, and can evaluate the subtle differences of the display 04 under different color displays, providing a more accurate basis for the color calibration and optimization of the display 04.

[0093] Quantum efficiency refers to the efficiency with which the sensor of a high-sensitivity camera 01 converts incident photons into electrons. When the quantum efficiency is greater than 80%, it means that more than 80% of the incident photons can be successfully converted into electrons, thereby forming a measurable electrical signal. This indicates that the high-sensitivity camera can utilize incident light more efficiently, capture more light information, and obtain high-quality sub-pixel region images.

[0094] The above describes the spectral testing system for sub-pixels of the display screen. The spectral testing method for this system is described below:

[0095] Please see Figure 5 The second aspect of this application provides a spectral testing method for sub-pixels of a display screen, applied to... Figures 1-4 The spectral testing system of any embodiment in the examples includes a spectral testing method comprising:

[0096] S1. In a dark room measurement environment, the display screen is lit up. The light signal on the display screen is optically amplified by the microscope objective and then split into a first optical path and a second optical path by the first beam splitter. The first optical path enters the hyperspectral analyzer and the second optical path enters the high-sensitivity camera.

[0097] To reduce the impact of ambient light on test results, in this embodiment, the display screen is lit up in a dark room measurement environment to put the display screen into normal working condition, and the sub-pixels emit light to generate light signals that can be tested.

[0098] According to the display screen specifications and testing requirements, provide appropriate power and control signals to make the display screen display specific test patterns (such as monochrome patterns such as all white, all red, all green, all blue, or complex patterns containing multiple colors) so as to test different sub-pixels.

[0099] The microscope objective has an optical magnification function, which can optically magnify the area it is aligned with to the sub-pixel level, that is, the sub-pixel outline can be clearly distinguished. The light from the sub-pixel enters the first beam splitter after being optically magnified by the microscope objective. After passing through the first beam splitter, the light is divided into a first optical path and a second optical path. The first optical path is introduced into the hyperspectral analyzer, and the second optical path is introduced into the high-sensitivity camera.

[0100] The hyperspectral analyzer processes the optical signal from the first optical path to obtain the spectral data of the sub-pixels. A high-sensitivity camera then captures an image of the sub-pixel region magnified by a microscope objective through the second optical path.

[0101] This application takes a display screen with a size of 2mm×2mm as an example for spectral testing. The size of the sub-pixels on the display screen is 5μm, so the total number of sub-pixels on the display screen is 160,000 (i.e., a 400×400 array).

[0102] S2. Synchronously adjust the working distance and aperture of the microscope objective until the high-sensitivity camera captures a clear image of the sub-pixels of the display screen;

[0103] The working distance of a microscope objective refers to the distance from the tip of the objective to the object being observed (in this case, a sub-pixel of the display screen). By adjusting the working distance, the microscope objective can be accurately focused on the sub-pixel of the display screen, thereby obtaining clear light signal acquisition.

[0104] The working distance can be changed by rotating the focusing ring on the microscope objective or by using a motorized focusing device. The aperture of the microscope objective is used to control the amount of light entering the microscope objective. The aperture size is adjusted according to the light emission characteristics of the display subpixels and the testing requirements to obtain appropriate image brightness and depth of field.

[0105] High-sensitivity cameras can capture images magnified by microscope objectives. The working distance and aperture of the microscope objectives are adjusted based on the image sharpness until sub-pixels are clear. A clear image means that the structure and boundaries of sub-pixels can be accurately represented, providing a reliable foundation for subsequent spectral analysis and image processing.

[0106] To ensure that the microscope objectives can meet the requirements for clear imaging of screen sub-pixels, the numerical aperture of the microscope objectives needs to be verified when selecting them.

[0107] The selection of microscope objective 03 in this embodiment meets the following conditions:

[0108] The Rayleigh criterion is used to verify the objective lens resolution. The Rayleigh criterion formula is as follows:

[0109] .

[0110] Where σ represents the minimum resolution distance (unit: μm), the minimum distance between two adjacent object points that can be distinguished (below this value, the image will be blurry), λ represents the center wavelength (unit: μm), the visible light range of the display screen is 550nm (0.55µm), and NA represents the numerical aperture of the microscope objective.

[0111] Since the subpixel size of the display screen is 5µm, to resolve subpixels of 5µm, σ≤5μm is required. Substituting this into the formula, we get:

[0112] 5 ≥ 0.61 × 0.55 ÷ NA;

[0113] That is: NA≥0.61×0.55÷5≈0.067.

[0114] Therefore, when selecting a microscope objective, a numerical aperture (NA) of ≥0.067 is sufficient. However, in actual subpixel spectral testing, to ensure clear imaging, a microscope objective with a larger numerical aperture (NA), such as NA ≥0.24, can be selected.

[0115] In addition, the working distance for adjusting the microscope objective lens must be ≥5mm.

[0116] S3. Perform dispersive spectroscopy on the first optical path using a hyperspectral analyzer and acquire spectral data of the current field of view;

[0117] A hyperspectral analyzer uses dispersive elements (such as gratings and prisms) to separate the polychromatic light incident in the first optical path according to wavelength, forming monochromatic light arranged by wavelength. The hyperspectral analyzer then introduces the polychromatic light from the first optical path into the dispersive elements, which spatially separate light signals of different wavelengths, forming a spectrum. The hyperspectral analyzer detects and records the dispersed light signals to acquire spectral data for the current field of view. This spectral data contains light intensity information at different wavelengths, reflecting the luminescence characteristics of sub-pixel regions of the display screen at different wavelengths.

[0118] A signal connection is established between the hyperspectral analyzer and the processing device, so when the hyperspectral analyzer acquires spectral data under the current field of view, it is transmitted to the processing device for storage.

[0119] S4. Image the second optical path using a high-sensitivity camera to obtain the image of the sub-pixel region corresponding to the current field of view.

[0120] A high-sensitivity camera acquires an image of the corresponding sub-pixel region within the current field of view. This image visually displays the distribution, shape, and color of the sub-pixels on the display screen, complementing the spectral data and providing a basis for comprehensive analysis of the display screen's performance.

[0121] The selection of a high-sensitivity camera in this embodiment meets the following conditions:

[0122] The formula for calculating the pixel resolution of a high-sensitivity camera is as follows:

[0123] Pixel resolution = camera pixel size / objective lens magnification.

[0124] To avoid information loss due to undersampling, a high-sensitivity camera's pixels must cover at least 2 pixels of the minimum resolvable distance. Furthermore, the pixel resolution of a high-sensitivity camera must satisfy the Nyquist sampling theorem. Therefore, we can derive:

[0125] Pixel resolution = Camera pixel size / Objective lens magnification ≤ .

[0126] Given a camera pixel size of σ = 3.45µm and a microscope objective magnification of 10x, the pixel resolution is calculated to be 3.45µm / 10 = 0.345µm.

[0127] Based on the numerical aperture NA=0.24 of the microscope objective actually selected above, σ≈1.4µm, therefore σ / 2=0.7µm; after comparison, it can be seen that 0.345µm<0.7µm, which satisfies the Nyquist sampling theorem.

[0128] S5. Based on the spectral data and image, the processing device generates a hyperspectral data cube containing the independent spectra of each sub-pixel in the current field of view.

[0129] A hyperspectral data cube is a three-dimensional data structure where two dimensions represent the spatial information of an image (i.e., the position of sub-pixels) and the other dimension represents the spectral information (the light intensity at different wavelengths). Using a hyperspectral data cube, the spatial distribution and spectral characteristics of sub-pixel regions of a display screen can be simultaneously acquired, providing detailed information for display screen quality inspection and performance evaluation.

[0130] In addition, the spectral data cube also includes grayscale values ​​(DN). Before acquiring the grayscale values, the acquired image undergoes grayscale correction, such as histogram equalization to enhance image contrast, and grayscale correction based on a reference image to more accurately adjust the grayscale distribution. After correction, the grayscale value (DN) of each pixel is directly read from the image data.

[0131] Therefore, through this application, a complete 4D (sub-pixel spatial location (x, y), visible light wavelength λ, gray value DN) spectral data can be obtained.

[0132] In the process of generating the hyperspectral data cube in this embodiment, the processing device first extracts sub-pixel features from the image, including shape (by obtaining the boundary through edge detection algorithms such as the Canny algorithm and then calculating the area, perimeter, aspect ratio, etc.), color (by using color space conversion, such as converting from RGB to HSV color space to extract color features), texture, and the previously obtained grayscale value DN. Based on the extracted sub-pixel features, a classification algorithm (such as support vector machine, neural network, etc.) is used to classify the sub-pixels. Different types of sub-pixels (red, green, blue) have different features, and the sub-pixel type is accurately identified by training a classification model. Image segmentation algorithms (such as threshold-based, region-based, or edge-based segmentation, etc.) are used to segment each sub-pixel from the image, and the segmented sub-pixel regions serve as the basic units for subsequent correlation analysis of spectral data and grayscale value DN.

[0133] Then, the processing device spatially matches the spectral data, grayscale value DN, and the segmented sub-pixel images. Based on the magnification of the microscope objective, the spectral characteristics of the first beam splitter, and camera imaging parameters, it establishes a spatial correspondence between the sub-pixel images and the spectral data and grayscale value DN, ensuring that the spectral data and grayscale value DN of each sub-pixel accurately correspond to its position in the image. Based on the spatial matching results, the spectral data and grayscale value DN of each sub-pixel are associated with image information such as the type and position of that sub-pixel. This forms a comprehensive data structure containing the sub-pixel spectrum, grayscale value DN, and image information.

[0134] The final processing device constructs a four-dimensional data cube, using the spatial location of sub-pixels (row coordinates x and column coordinates y) as two dimensions, spectral wavelength as a third dimension, and grayscale value DN as a fourth dimension. In this data cube, each "supervoxel" (the smallest unit in four-dimensional space) corresponds to the spectral intensity value of a specific sub-pixel at a specific wavelength and the grayscale value DN of that sub-pixel at the corresponding position. Based on the previously associated sub-pixel spectral data, grayscale value DN, and image information, the spectral intensity value and grayscale value DN of each sub-pixel are filled into the corresponding positions in the data cube. For each sub-pixel, its spectral data is filled along the spectral wavelength dimension and its grayscale value is filled along the DN dimension, thus forming a complete hyperspectral data cube containing the independent spectrum and grayscale value DN of each sub-pixel.

[0135] In this embodiment, by using the precise focusing of the microscope objective and the high spectral resolution of the hyperspectral analyzer, it is possible to perform fine spectral testing on the sub-pixels of the display screen, accurately obtain the spectral characteristics of the sub-pixels, and solve the technical problem that traditional technologies cannot perform sub-pixel-level spectral testing.

[0136] To perform spectral testing on the entire display screen, the screen needs to be moved during the testing process until the entire screen area has been tested. The specific details are as follows:

[0137] Please continue reading. Figure 6 This application provides another embodiment of a spectral testing method for sub-pixels of a display screen, which includes performing the following steps after step S2:

[0138] S6. Based on the field of view of the microscope objective, calculate the single step distance of the test platform along the width and height of the display screen, respectively, and place the display screen on the test platform;

[0139] Field of view (FOP) refers to the size of the area that a microscope objective can observe on a display screen, usually expressed as length and width, such as 100μm × 100μm. FOP determines the range of subpixels on the display screen that can be captured in each test. A larger FOP allows for a larger area to be captured each time, but at the cost of some resolution; a smaller FOP allows for a more detailed area to be captured, but requires more steps to cover the entire display screen.

[0140] The single step distance refers to the distance the test platform moves the display screen in each horizontal or vertical direction. It determines the degree of overlap between adjacent test areas and the number of steps required to cover the entire display screen. Adjacent test areas are defined as those that are physically adjacent. The calculation can be based on the field of view of the microscope objective and the required overlap rate. For example, if there is a 10% overlap between adjacent test areas, the single step distance can be calculated using the following formula:

[0141] Step distance = Field of view size × (1 - Overlap rate). Assuming a field of view size of 0.64mm × 0.48mm and an overlap rate of 10%, the horizontal single step distance (X) is 0.64 × (1% - 10%) = 0.576mm, and the vertical single step distance (Y) is 0.48 × (1% - 10%) = 0.432mm. To capture the entire display screen (2mm × 2mm), the total number of shots is: 4 (horizontal X) × 5 (vertical Y) = 20.

[0142] In this embodiment, the number of sub-pixels covered in a single instance is:

[0143] Sub-pixels.

[0144] Additionally, the movement interval time needs to be determined. The movement interval time refers to the waiting time between each movement of the test platform and the start of the next test. Before moving, it is necessary to ensure that the high-sensitivity camera has completed exposure and stabilization, and that the spectral test of the current field of view has been completed before proceeding to the next movement and test. S7. Control the display screen to move according to the step distance through the test platform. After each movement is completed, execute steps S3-S5 to obtain a cube of hyperspectral data for multiple fields of view until the entire display screen area is covered; then execute step S8.

[0145] The movement error of the test platform when controlling the display screen movement must be ≤±1μm to ensure splicing accuracy. After each display screen is moved into place, the hyperspectral data cube is acquired according to the operation process of steps S3, S4, and S5, thereby obtaining hyperspectral data cubes of multiple sub-pixel regions of the display screen.

[0146] Steps S3, S4, and S5 have been described in detail in the foregoing embodiments and will not be repeated here.

[0147] Repeat the above test operation until the entire display area is covered. Specifically, this can be determined by recording the number of steps moved and the position information, and comparing this data with the pre-calculated number of steps and the total size of the display. If the entire area is not yet covered, continue moving the display and collecting data in increments until the entire display area is covered. For example, if the pre-calculated number of steps required is 4 horizontal moves and 5 vertical moves, totaling 4 x 5 = 20 steps, then compare the current number of steps moved with this 20. If less than 20 steps have been reached, continue moving the display until the entire display area is covered.

[0148] Please see Figure 4 During the controlled movement of the display screen, the test platform controls the screen to move from left to right and from top to bottom. Specifically, the screen is initially positioned at the leftmost starting position (at which point the microscope objective is aligned with the lower right corner of the screen). After acquiring the spectral data and image at the starting position, the screen moves horizontally to the right. For each step (the step size should be determined based on the field of view width of the microscope objective to ensure a certain overlap between adjacent moves to avoid missed detections), data (spectral data and image) is acquired. When the screen moves to the rightmost position (at which point the microscope objective is aligned with the lower left corner of the screen), it moves vertically downwards by one line spacing (also determined based on the field of view height and overlap requirements), and then scans the next line from right to left. This process is repeated until the entire screen is scanned.

[0149] S8. By processing the hyperspectral data cubes of all fields of view, a full-area sub-pixel spectral distribution map of the display screen is generated.

[0150] Since there is some overlap between adjacent test areas, the spectral characteristics of the overlapping areas can be used for matching to determine the relative positional relationship between hyperspectral data cubes at different locations. For example, by calculating the spectral correlation of the overlapping areas, the location with the highest correlation can be found, thereby determining the offset for data stitching.

[0151] The SIFT algorithm was used to match overlapping regions, and multiple hyperspectral images were stitched together to form a complete 2mm×2mm image.

[0152] The acquired hyperspectral images were stitched together to obtain a complete hyperspectral image of the display screen. The spectral curve of each sub-pixel was output by the hyperspectral analyzer in the format: DN(x, y, λ) (x, y: 0~399, λ: 400~700nm). Then, the spectral curve of each sub-pixel was extracted to provide data support for subsequent spectral analysis and research.

[0153] In this embodiment, the purpose of stitching is to combine individual hyperspectral data cubes into a complete dataset to reflect the spectral distribution of sub-pixels across the entire display screen. Specifically, data stitching can be performed using methods based on feature matching or coordinate alignment. Feature points (such as abrupt changes in spectral intensity, peak points at specific wavelengths, etc.) in adjacent fields of view (positionally adjacent) of hyperspectral data cubes are extracted, and then stitched according to the correspondence of these feature points. The coordinate alignment method involves aligning the coordinates of each hyperspectral data cube based on the step distance and initial position information of the test platform, thereby achieving stitching. After data stitching is completed, the processing device generates a global sub-pixel spectral distribution map of the display screen based on the stitched complete dataset. This spectral distribution map visually displays the spectral intensity distribution of each sub-pixel on the display screen at different wavelengths. Through this spectral distribution map, the luminescence of each sub-pixel on the display screen at different positions and wavelengths can be intuitively observed, providing important reference for the performance evaluation and optimization of the display screen.

[0154] In this embodiment, by moving the display screen through the test platform and conducting multiple tests, the entire area of ​​the display screen can be covered, avoiding test blind spots caused by the limitation of the field of view size, and realizing comprehensive detection of the spectral characteristics of the sub-pixels of the display screen.

[0155] By stitching together data collected from multiple locations, a three-dimensional spectral spatial distribution map is generated that can accurately reflect the spectral spatial distribution of sub-pixels on the display screen.

[0156] Please continue reading. Figure 7 In an optional embodiment, after step S8, the spectral testing method further includes:

[0157] The S9 processing device constructs an interactive visualization interface based on the global sub-pixel spectral distribution map.

[0158] In this step, common programming languages ​​(such as Python and JavaScript) and relevant visualization frameworks (such as Matplotlib and D3.js) can be used to build an interactive visualization interface. The data from the global sub-pixel spectral distribution map is bound to the visualization elements, ensuring that user actions on the interface are reflected in the data in real time, and that data updates are displayed promptly on the interface. For example, when a user clicks on a sub-pixel, the spectral curve of that sub-pixel can be extracted from the data and plotted in the spectral curve display area through programming.

[0159] In the visualization elements, appropriate graphic elements are used to represent subpixels, such as small squares and circles. Different colors can be used to distinguish subpixel types (e.g., red, green, blue). A reserved area in the interface is used to display the spectral curve of the user-selected subpixel. This area can be in the form of a coordinate system, with the horizontal axis representing wavelength and the vertical axis representing spectral intensity, clearly showing the spectral characteristics of the subpixel at different wavelengths. Wavelength range selection tools are provided, such as sliders and input boxes, allowing users to select the wavelength range of interest by dragging the slider or entering specific wavelength values.

[0160] S10. In response to the user clicking on the location of the interactive visualization interface, extract the spectral curve of the corresponding sub-pixel from the global sub-pixel spectral distribution map and display it;

[0161] When a user clicks on the interactive visual interface, the processing device accurately detects the location of the click. This can be achieved through event handling mechanisms in interface programming, such as using a click event in JavaScript to capture the user's click action and obtaining the coordinates of the click through the event object's properties. Based on the detected click location, combined with the spatial location information of sub-pixels in the global sub-pixel spectral distribution map, the device determines which sub-pixel the user clicked. Once the clicked sub-pixel is determined, the processing device extracts the spectral curve of that sub-pixel from the data in the global sub-pixel spectral distribution map. Then, the extracted spectral curve is plotted and displayed in a pre-defined spectral curve display area.

[0162] And / or in response to the wavelength range selected by the user in the interactive visualization interface, display the corresponding display area within the selected wavelength range.

[0163] When a user selects a wavelength range of interest using the wavelength range selection tool, the processing device acquires the wavelength range value entered by the user, which can be achieved by reading the value of the slider or the value in the input box. Based on the acquired wavelength range, the processing device filters out the corresponding display area within that wavelength range from the global sub-pixel spectral distribution map. Within the corresponding display area, the spectral data of each sub-pixel can be further traversed and evaluated to determine which sub-pixels have higher spectral intensity or other relevant characteristics within the selected wavelength range. Then, the filtered areas are highlighted on the visualization interface, for example, by using different colors, brightness levels, or borders to mark these areas so that the user can see them clearly.

[0164] In this embodiment, an interactive visualization interface is constructed to display complex spectral data in an intuitive graphical manner, enabling users to quickly understand the spectral distribution of sub-pixels on the display screen. Users can obtain key information without tedious data queries and analysis, greatly improving the efficiency of data analysis. By allowing users to click on sub-pixels to view their spectral curves and select wavelength ranges to view corresponding areas, users can quickly locate sub-pixels or areas that may have problems. For example, if an abnormal spectral curve of a sub-pixel is found, users can further analyze the sub-pixel's condition, thereby promptly identifying and resolving display screen quality issues.

[0165] In another optional embodiment, step S2 further includes: setting a second beam splitter in the optical path between the microscope objective and the high-sensitivity camera, and splitting a third optical path from the optical path between the microscope objective and the high-sensitivity camera through the second beam splitter; setting an observation device in the third optical path, and the third optical path entering the observation device; and adjusting the working distance and aperture of the microscope objective by the imaging sharpness of the sub-pixels of the display screen in the observation device.

[0166] In this embodiment, the second beam splitter can be positioned between the high-sensitivity camera and the first beam splitter, or between the microscope objective and the first beam splitter. The second beam splitter divides the light into a third optical path, which is then introduced into the observation device. Here, a bright-field camera or a trinocular tube is used as the observation device. The light signal from the third optical path enters the bright-field camera or trinocular tube, and the image of the sub-pixels on the display screen can be observed through the bright-field camera or trinocular tube.

[0167] The positional relationship between the first and second beam-splitting elements has been described in detail previously and will not be repeated here. During the adjustment process, it is necessary to observe the image captured by the bright-field camera or trinocular lens in real time until the image reaches a clear state (MTF≥30%).

[0168] In this application, a microscope objective, a hyperspectral analyzer, and a high-sensitivity camera are used in combination to test the spectrum of each sub-pixel of the entire display screen. Furthermore, this method is applicable to testing sub-pixel spectra under low-brightness conditions.

Claims

1. A spectral testing system for sub-pixels of a display screen, characterized in that, include: High-sensitivity camera, hyperspectrometer, processing equipment, first spectroscopic element, and microscope objective; The microscope objective is aligned with the surface of the display screen to optically magnify the sub-pixel region of the display screen to the sub-pixel level. The first beam splitter is located at the optical output end of the microscope objective, splitting the magnified light signal into a first optical path and a second optical path. The first optical path is input to the hyperspectral analyzer, which performs dispersive spectral analysis on the first optical path and records spectral data. The second optical path is input to the high-sensitivity camera, which acquires an image of the sub-pixel region. The processing device is connected to the hyperspectral analyzer and the high-sensitivity camera, respectively, and generates a hyperspectral data cube containing the spectrum of a single sub-pixel based on the spectral data and the image. The hyperspectral analyzer has a spectroscopic range of 400-700nm and a spectral resolution of ≤5nm. The quantum efficiency of the high-sensitivity camera is >80%; The spectral testing system also includes a testing platform located below the microscope objective, which is used to support and fix the display screen. The test platform includes a fixed frame, a movable plate, and a two-dimensional drive component; the movable plate is disposed above the fixed frame, and the two-dimensional drive component is disposed between the movable plate and the fixed frame. The two-dimensional drive component is signal-connected to the processing device, and the two-dimensional drive component is controlled to drive the movable plate to move at a preset step distance. The processing device includes a motion control module and a stitching module; the motion control module is signal-connected to the two-dimensional driving component, and the stitching module is signal-connected to the high-sensitivity camera and the hyperspectral analyzer, respectively. The stitching module is used to stitch together the image and spectral data of adjacent sub-pixel regions.

2. The spectral testing system according to claim 1, characterized in that, The spectral testing system further includes a second spectroscopic element and an observation device. The second spectroscopic element is disposed in the optical path between the microscope objective and the high-sensitivity camera. The second spectroscopic element is used to split a third optical path from the optical path between the microscope objective and the high-sensitivity camera. The observation device is disposed in the third optical path.

3. The spectral testing system according to claim 2, characterized in that, The observation device is a bright-field camera or a trinocular telescope.

4. A method for spectral testing of sub-pixels of a display screen, applied to the spectral testing system according to any one of claims 1 to 3, characterized in that, The spectral testing method includes the following steps: S1. In a dark room measurement environment, the display screen is lit up. The sub-pixel light signal on the display screen is optically magnified by the microscope objective and then split into a first optical path and a second optical path by the first beam splitting element. The first optical path enters the hyperspectral analyzer and the second optical path enters the high-sensitivity camera. S2. Synchronously adjust the working distance and aperture of the microscope objective until the high-sensitivity camera captures a clear image of the sub-pixel area of ​​the display screen; S3. Perform dispersive spectroscopy on the first optical path using a hyperspectral analyzer and acquire spectral data of the current field of view; S4. Image the second optical path using a high-sensitivity camera to obtain an image of the sub-pixel region corresponding to the current field of view; S5. Based on the spectral data and the image, the processing device generates a hyperspectral data cube containing the independent spectra of each sub-pixel in the current field of view; Following step S2, the spectral testing method further includes the following steps: S6. Based on the field of view of the microscope objective, calculate the single step distance of the test platform along the width and height of the display screen, respectively, with the display screen placed on the test platform; S7. Control the display screen to move according to the step distance through the test platform. After each movement is completed, execute steps S3-S5 to obtain the hyperspectral data cube with multiple fields of view until it covers the entire display screen area; then execute step S8. S8. The hyperspectral data cubes of all fields of view are stitched together by the processing device to generate a global sub-pixel spectral distribution map of the display screen.

5. The spectral testing method according to claim 4, characterized in that, Following step S8, the spectral testing method further includes the following steps: S9. The processing device constructs an interactive visualization interface based on the global sub-pixel spectral distribution map; S10. In response to the user clicking on the location of the interactive visualization interface, extract the sub-pixel spectral curve corresponding to the location from the global sub-pixel spectral distribution map and display it; And / or in response to a wavelength range selected by the user in the interactive visualization interface, display the corresponding display area within the wavelength range.

6. The spectral testing method according to claim 4, characterized in that, Step S2 further includes: A second beam splitter is provided in the optical path between the microscope objective and the high-sensitivity camera, and a third optical path is split from the optical path between the microscope objective and the high-sensitivity camera by the second beam splitter; an observation device is provided in the third optical path, and the third optical path enters the observation device; The working distance and aperture of the microscope objective are adjusted by the imaging sharpness of the sub-pixels of the display screen in the observation device.

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