A distortion picture correction method and display device

Abstract

The embodiment of the present invention discloses a method for correcting a distorted image and a display device. The correction method includes: obtaining a captured image of a standard correction pattern displayed by a display device; preprocessing the captured image to extract the coordinates of feature points in the captured image; selecting a preset number of feature points in the central area of ​​the captured image, adjusting the rotation and scale of the captured image according to the selected feature points, and obtaining a corrected image; calculating the offset of each feature point of the corrected image relative to the corresponding position of the standard correction pattern according to the corrected image and the standard correction pattern; and correcting the actual display image of the display device according to the offset. The distorted image correction method provided by the embodiment of the present invention can be used to correct the irregular distortion generated by a near-eye display device after refraction by an optical structure, thereby improving the user experience.

Description

Technical Field

[0001] The embodiments of the present invention relate to display technology, and in particular to a distortion picture correction method and a display device. Background Art

[0002] In the imaging process of various optical imaging systems, various distortions are inevitably generated. The existing technology generally corrects the distortion according to a pre-set formula, fits the distortion coefficient, and achieves the offset of the deformation effect. The traditional de-distortion algorithm is usually used to correct the distortion caused by various optical imaging lenses. This type of distortion has a relatively clear distortion effect, such as pincushion distortion, barrel distortion, etc.

[0003] Using the method of fitting the distortion coefficients using formulas, complex distortion effects correspond to complex correction models. The prior knowledge of the distortion type helps select a suitable correction model and further helps improve the correction effect of the picture. Currently, mainstream distortion correction algorithms are mostly used to process the picture distortion caused by optical imaging modules, and the default distortion effect is rotationally symmetric. However, some near-eye display devices (such as wearable virtual reality VR devices, augmented reality AR devices, etc.) will cause irregular distortion of the virtual image after refraction through the optical structure. The distortion effect is similar to the effect caused by the combined effects of multiple distortion types. It is difficult to use conventional coefficient fitting methods to achieve anti-distortion processing of the picture, which affects the user experience. Summary of the invention

[0004] The embodiments of the present invention provide a distorted image correction method and a display device. The correction method can be used to correct irregular distortion of a near-eye display device after refraction through an optical structure, thereby improving user experience.

[0005] In a first aspect, an embodiment of the present invention provides a method for correcting a distorted image, comprising:

[0006] S1, obtaining a photographic image of a standard calibration pattern displayed on a display device;

[0007] S2, preprocessing the captured image to extract coordinates of feature points in the captured image;

[0008] S3, selecting a preset number of feature points in the central area of ​​the captured image, and adjusting the rotation and scale of the captured image according to the selected feature points to obtain a corrected image;

[0009] S4, calculating, according to the correction picture and the standard correction pattern, the offset of each feature point of the correction picture relative to the corresponding position of the standard correction pattern;

[0010] S5. Correct the actual display image of the display device according to the offset.

[0011] Optionally, also include:

[0012] The loop executes S1 to S4 for a preset number of times until the loop termination condition is reached.

[0013] Optionally, the loop termination condition includes that the number of loops exceeds a preset maximum value or the maximum offset of the feature point is less than a preset threshold value.

[0014] Optionally, obtaining a captured image of a standard calibration pattern displayed by a display device includes:

[0015] Fixing the display device on a fixture table;

[0016] Controlling the display device to display a standard calibration pattern;

[0017] The shooting camera is fixed at the position of the fixture slot, and the standard calibration pattern is photographed and stored to obtain the shooting picture.

[0018] Optionally, the standard calibration pattern includes a plurality of white display areas arranged in an array;

[0019] Preprocessing the captured image to extract coordinates of feature points in the captured image includes:

[0020] Performing contrast enhancement on the captured image and removing discrete noise points by using morphological opening operation;

[0021] Calculating the grayscale change gradients of adjacent pixels in a first direction and a second direction, and selecting the side where the pixel with the largest grayscale change gradient is located as the boundary of the white display area;

[0022] Taking the coordinates of the center point of the white display area as the coordinates of the feature point;

[0023] The first direction is parallel to the row direction of the array formed by the white display areas, and the second direction is parallel to the column direction of the array formed by the white display areas.

[0024] Optionally, the shape of the white display area includes rectangle, circle or triangle.

[0025] Optionally, before preprocessing the captured image, the method further includes:

[0026] The shooting camera performs distortion correction on the captured image.

[0027] Optionally, selecting a preset number of feature points in the central area of ​​the captured image, and adjusting the rotation and scale of the captured image according to the selected feature points to obtain a corrected image, including:

[0028] Selecting 6×6 feature point coordinates in the central area of ​​the photographed image, and calculating a rotation angle and a scaling scale of the photographed image relative to the standard calibration pattern;

[0029] The captured image is adjusted according to the rotation angle and the zoom scale to obtain the corrected image.

[0030] Optionally, calculating the offset of each feature point in the standard calibration pattern according to the correction image and the standard calibration pattern includes:

[0031] Filling the central area of ​​the correction image to form a correction pattern with the same size as the standard correction pattern;

[0032] The calibration pattern and the standard calibration pattern are aligned according to the central area, and the offset of each feature point outside the central area is counted.

[0033] Optionally, correcting the actual display image of the display device according to the offset includes:

[0034] The original texture image displayed by the display device is stretched, shrunk and affine transformed according to the offset using a graphics rendering interface, and then remapped to a display area corresponding to the display device to achieve actual display image correction.

[0035] In a second aspect, an embodiment of the present invention further provides a display device, comprising a display device and a distorted image correction device, wherein the distorted image correction device pre-stores the offset of each feature point obtained by the above-mentioned distorted image correction method, and the distorted image correction device is used to correct the display image output by the display device according to the offset.

[0036] Optionally, the display device includes a wearable display device based on a silicon-based display.

[0037] The distortion picture correction method provided by the embodiment of the present invention first controls the display device to display the standard correction pattern, and shoots the picture of the standard correction pattern; then pre-processes the picture, extracts the coordinates of the feature points in the picture; then selects a preset number of feature points in the central area of ​​the picture, rotates and resizes the picture according to the selected feature points, and obtains a corrected picture; calculates the offset of each feature point of the correction pattern relative to the corresponding position of the standard correction pattern according to the corrected picture and the standard correction pattern; finally, corrects the actual display picture of the display device according to the offset. The technical solution of the embodiment of the present invention is to design and project a specific standard correction pattern for the various uncertain factors that may exist in the display device to affect the display picture, shoot the display device through a camera, simulate the actual viewing effect of the user, and after a series of image processing technologies, based on the assumption that there is no significant distortion in the center of the picture, align the standard correction pattern with the processed corrected picture, find the offset of the corresponding key point, and reversely modify the coordinate position of each key point in proportion to achieve picture correction and improve user experience. BRIEF DESCRIPTION OF THE DRAWINGS

[0038] Figure 1 A schematic diagram of a flow chart of a method for correcting a distorted image provided by an embodiment of the present invention;

[0039] Figure 2 A schematic diagram of a standard calibration pattern provided by an embodiment of the present invention;

[0040] Figure 3 A schematic diagram of the offset in the distortion picture correction method provided by an embodiment of the present invention;

[0041] Figure 4 A schematic flow chart of another distortion correction method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0042] The present invention will be further described in detail below in conjunction with the accompanying drawings and embodiments. It is to be understood that the specific embodiments described herein are only used to explain the present invention, rather than to limit the present invention. It should also be noted that, for ease of description, only parts related to the present invention, rather than all structures, are shown in the accompanying drawings.

[0043] The terms used in the embodiments of the present invention are only for the purpose of describing specific embodiments and are not intended to limit the present invention. It should be noted that the directional words such as "upper", "lower", "left", "right" and the like described in the embodiments of the present invention are described at the angles shown in the accompanying drawings and should not be understood as limitations on the embodiments of the present invention. In addition, in the context, it is also necessary to understand that when it is mentioned that an element is formed "on" or "under" another element, it can not only be directly formed "on" or "under" another element, but also indirectly formed "on" or "under" another element through an intermediate element. The terms "first", "second" and the like are only used for descriptive purposes and do not indicate any order, quantity or importance, but are only used to distinguish different components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to the specific circumstances.

[0044] Figure 1 A flowchart of a method for correcting a distorted image provided by an embodiment of the present invention is shown in FIG. Figure 1 The distortion image correction method provided in this embodiment includes:

[0045] S1. Acquire a photographic image of a standard calibration pattern displayed on a display device.

[0046] The display device in the embodiment of the present invention may be a near-eye display device, such as a VR or AR device. The standard calibration pattern may be a preset black and white pattern, such as a checkerboard pattern, and the captured image may be acquired using a camera. Optionally, acquiring the captured image of the standard calibration pattern displayed by the display device includes:

[0047] S11. Fix the display device on the fixture table.

[0048] The fixture table can be customized according to the display device, and a card slot for fixing the shooting camera is set at a specific position. The shooting camera is used to simulate the human eye. The specific implementation can be designed according to actual conditions, and the embodiment of the present invention is not limited.

[0049] S12, controlling the display device to display a standard calibration pattern.

[0050] The standard correction pattern may be a black and white pattern, for example, including a plurality of white display areas arranged in an array (in a specific implementation, the white display area may be a white square, each white square is composed of a plurality of pixels displayed as white), and black intervals are provided between the white display areas, and the black intervals include a plurality of pixels displayed as black. The specific number of white display areas may be manually set by the operator. If the number is too small, some areas of the corrected image may have obvious excessive effects, and the correction effect may be poor; if the number is too large, the system errors in the subsequent image processing steps may significantly affect the final correction effect. For example, Figure 2A schematic diagram of a standard calibration pattern provided in an embodiment of the present invention. In this embodiment, after weighing the two, 32×32 evenly arranged white squares with black intervals between the white squares are selected as the standard calibration pattern. In other embodiments, the standard calibration pattern does not limit the number of white squares, nor is it limited to the use of squares. For example, it can be a rectangle, a circle, or a triangle. The characteristic pattern in the specific calibration pattern (the white square in this embodiment) is selected to be a type that is easy for the computer language to search, and the geometric center of the characteristic pattern is consistent with the segmentation point after the pattern is proportionally cut. In some embodiments, the standard calibration pattern is not limited to a black and white pattern. For example, multiple red squares can be set, and green intervals are set between the red squares. It can be flexibly set according to actual conditions during implementation.

[0051] S13, fixing the shooting camera at the position of the fixture card slot, and shooting and storing the standard calibration pattern to obtain a shooting picture.

[0052] The specific shooting camera can be selected according to actual conditions, and the embodiment of the present invention does not limit this.

[0053] S2. Preprocess the captured image to extract the coordinates of feature points in the captured image.

[0054] The characteristic points in the captured image are the geometric centers of the characteristic patterns (eg, the white squares in this embodiment).

[0055] Preprocessing the captured image and extracting the coordinates of feature points in the captured image include:

[0056] S21, enhancing the contrast of the captured image and removing discrete noise points using morphological opening operation.

[0057] It is understandable that the picture taken by the camera may appear darker or brighter overall. This is because the grayscale value range of the picture is small, that is, the contrast is low. For low-contrast pictures, the contrast enhancement technology can be used to enlarge the grayscale level of the picture to a specified degree. For example, if the grayscale range of the camera picture is 200-250, the algorithm can be used to stretch the contrast range of the picture to 100-250, thereby achieving contrast enhancement. Specific contrast enhancement methods include linear transformation, piecewise linear transformation, gamma transformation, histogram normalization, histogram equalization, local adaptive histogram equalization, etc., which can be selected according to actual conditions during specific implementation. After contrast enhancement, due to the grayscale enlargement, some discrete white noise may appear in the black interval area. Then, the morphological opening operation is performed, which has the function of eliminating small objects, separating objects in thin places and smoothing the boundaries of larger objects, and can remove discrete noise in the captured picture. The morphological opening operation includes the operation of first erosion and then expansion. The definition of structure A being eroded by structure B is: move structure B. If the intersection of structure B and structure A completely belongs to the area of ​​structure A, then save the position point. All points that meet the conditions constitute the result of structure A being eroded by structure B. The definition of structure A being expanded by structure B is: perform a convolution operation on structure B on structure A. If there is an overlapping area with structure A during the process of moving structure B, then record the position. The set of all positions where the moving structure B and structure A have an intersection is the expansion result of structure A under the action of structure B. Specifically, in this embodiment, the picture is firstly corroded, specifically, the picture pixels are traversed, and some white pixels are at the edge of the white square and adjacent to the black pixels, and such white pixels are modified to black; then the dilation operation is performed, and the black pixels adjacent to the white pixels are modified to white again. Because the white area corresponding to the noise is relatively small, the entire area will be directly eliminated after the corrosion step and will not be further expanded. The area corresponding to the white square in the standard correction pattern is relatively large, and some white pixels are still retained after corrosion, and then further dilation operation will restore it to the initial state, thereby achieving effective elimination of white noise without affecting the standard correction pattern.

[0058] S22, calculating the grayscale change gradients of adjacent pixels in the first direction and the second direction, and selecting the side where the pixel with the largest grayscale change gradient is located as the boundary of the white display area.

[0059] The first direction is parallel to the row direction of the array formed by the white display area, and the second direction is parallel to the column direction of the array formed by the white display area. Each white display area includes a plurality of pixels displayed as white, and the black interval includes a plurality of pixels displayed as black. If two adjacent pixels are both displayed as white or both displayed as black, the grayscale change gradient of the two pixels is small. If one of the two adjacent pixels is displayed as white and the other is displayed as black, the grayscale change gradient of the two pixels is large. Therefore, the pixel at the boundary of the white display area can be found according to the grayscale change gradient as the boundary of the white display area, thereby determining the size of the white display area. The grayscale change gradient of the pixel is defined as Where f(x) represents the grayscale value of the corresponding pixel, f(x+1) and f(x-1) represent the grayscale values ​​of two pixels adjacent to the corresponding pixel in the first direction or the second direction, and f′(x) represents the grayscale change gradient of the corresponding pixel position. The position with the largest grayscale change gradient indicates that white and black have jumped, which is the boundary position of the white display area.

[0060] S23. Taking the coordinates of the center point of the white display area as the coordinates of the feature point.

[0061] When processing the captured image, a corresponding rectangular coordinate system can be established based on the image. After obtaining the boundary of the white display area based on the pixel grayscale change gradient, for example, for a white square, the coordinates of the four vertices of the white square can be calculated. In this embodiment, the geometric center of the white square is used as the feature point. After the position of each white square is determined, the coordinates of the feature point can be calculated, and the feature point is used as a reference position for subsequently obtaining the offset.

[0062] S3. Select a preset number of feature points in the central area of ​​the captured image, and adjust the rotation and scale of the captured image according to the selected feature points to obtain a corrected image.

[0063] For the images captured by the camera, the central area is generally less likely to be distorted than the edge area. In this embodiment, based on the assumption that the central area is free of distortion, the feature points in the central area are used as a reference. Specifically, in a certain embodiment, a preset number of feature points in the central area of ​​the captured image are selected, and the rotation and scale of the captured image are adjusted according to the selected feature points to obtain a corrected image, including:

[0064] S31 , selecting 6×6 feature point coordinates in the central area of ​​the captured image, and calculating the rotation angle and scaling scale of the captured image relative to the standard calibration pattern.

[0065] It is understandable that the image captured by the camera is not exactly the same as the image displayed by the display device. There may be a certain rotation angle and scaling ratio. In this embodiment, the coordinates of 6×6 feature points in the central area of ​​the captured image are selected and compared with the standard calibration pattern to calculate the rotation angle and scaling ratio of the captured image. The image slope b and scale Scale calculation formulas are:

[0066] where x i ,y i 、x max and x min is the coordinate data in the shooting picture, and is the coordinate data in the standard calibration pattern.

[0067] S32, adjusting the captured image according to the rotation angle and the zoom scale to obtain a corrected image.

[0068] For example, when processing a captured image, if it is calculated that the captured image is rotated clockwise by a certain angle relative to the original image, the captured image is rotated counterclockwise; if it is calculated that the captured image is enlarged by a certain multiple relative to the original image, it is necessary to infer the proportion that needs to be reduced based on the proportion of the captured image and adjust the captured image.

[0069] S4. Calculate the offset of each feature point of the correction image relative to the corresponding position of the standard correction pattern according to the correction image and the standard correction pattern.

[0070] Among them, the corrected image is obtained by photographing the standard calibration pattern with a camera and processing it. Due to the influence of image distortion, each feature point in the corrected image will have a certain offset relative to the corresponding position of the standard calibration pattern (for points without offset, the offset is 0). The corrected image and the standard calibration pattern are aligned, and according to the same coordinate system, the offset of each feature point can be calculated based on the feature points of the corrected image and the coordinates of the corresponding positions in the standard calibration pattern.

[0071] Optionally, calculating the offset of each feature point in the standard calibration pattern according to the correction image and the standard calibration pattern includes:

[0072] S41, filling the central area of ​​the correction image to the surrounding areas to form a correction pattern with the same size as the standard correction pattern.

[0073] In this embodiment, it is assumed that the central area has no distortion. Since the standard correction pattern is a regular pattern, the patterns in each area are the same. The pattern in the central area of ​​the correction image can be expanded outward to form a correction pattern. By replacing the pattern in the peripheral area with the image in the central area, it is possible to avoid large extraction errors of feature point coordinates due to large distortion of the image in the peripheral area, which is conducive to improving the accuracy of offset calculation.

[0074] S42: aligning the calibration pattern and the standard calibration pattern according to the central area, and counting the offset of each feature point outside the central area.

[0075] The offset of the feature point is calculated according to difference(i,j)=(Δx ij ,Δy ij ), where i and j are integers, Δx ij and Δ yij is the offset in the row and column directions. In the specific implementation, considering the existence of errors, the result of a single calculation may be biased. In order to eliminate the influence of a single error on the final result as much as possible, this solution can use an iterative solution method to calculate the cumulative result of the offset value.

[0076] For example, Figure 3 A schematic diagram of the offset in the distortion picture correction method provided by an embodiment of the present invention, Figure 3 Twelve white squares are schematically shown in the figure, where the edge of the characteristic pattern in the correction pattern is represented by a dotted line, the center of the white square in the standard correction pattern is A, and the center of the white square in the corresponding correction pattern is B. The oblique line segment AB represents the offset of the characteristic point B, and the other offsets in the figure are all represented by corresponding written line segments.

[0077] S5. Correct the actual display image of the display device according to the offset.

[0078] After calculating the offset of each feature point, the feature pattern where the feature point is located and the adjacent partial black interval (for example, the area surrounding the feature pattern and occupying half the width of the black interval) can be used as a correction area, and all pixel points in the correction area use the offset of the corresponding feature point to correct the image.

[0079] Optionally, correcting the actual display image of the display device according to the offset includes:

[0080] The original texture image displayed by the display device is stretched, shrunk and affine transformed according to the offset using a graphics rendering interface, and then remapped to the display area of ​​the corresponding display device to achieve actual display image correction.

[0081] In this embodiment, the actual image of the display device is corrected based on the rendering characteristics of OpenGL texture mapping to improve the user experience.

[0082] The technical solution of the embodiment of the present invention is to first control the display device to display the standard calibration pattern and shoot the shooting picture of the standard calibration pattern; then pre-process the shooting picture to extract the coordinates of the feature points in the shooting picture; then select a preset number of feature points in the central area of ​​the shooting picture, rotate and scale the shooting picture according to the selected feature points to obtain a corrected picture; calculate the offset of each feature point of the corrected picture relative to the corresponding position of the standard calibration pattern according to the corrected picture and the standard calibration pattern; finally, correct the actual display picture of the display device according to the offset. The technical solution of the embodiment of the present invention is to design and project a specific standard calibration pattern in view of the various uncertain factors that may exist in the display device and affect the display picture, shoot the display device through a camera, simulate the actual viewing effect of the user, and after a series of image processing technologies, based on the assumption that there is no significant distortion in the center of the picture, align the standard calibration pattern with the processed corrected picture, find the offset of the corresponding key point, and then reversely modify the coordinate position of each key point in proportion to achieve picture correction and improve user experience.

[0083] Optionally, the distortion correction method provided by the embodiment of the present invention further includes:

[0084] The loop executes S1 to S4 for a preset number of times until the loop termination condition is reached.

[0085] Optionally, the loop termination condition includes that the number of loops exceeds a preset maximum value or the maximum offset of the feature point is less than a preset threshold value.

[0086] Figure 4 A flowchart of another distortion correction method provided by an embodiment of the present invention is shown in FIG. Figure 4 First, the display device is fixed on the fixture table, and the display device is controlled to display a standard calibration pattern, wherein the display device can be a near-eye display device such as AR or VR, and the standard calibration pattern can be Figure 2The pattern shown. The shooting camera is then fixed at the position of the fixture slot, and the standard calibration pattern is photographed and stored to obtain a shooting picture. After obtaining the shooting picture, the shooting camera performs distortion correction on the shot picture. Among them, the distortion correction of the shooting camera is the correction of the picture performed by the shooting camera based on the existing technology. Then the contrast of the shooting picture is enhanced, and the discrete noise is removed by morphological opening operation. The contrast enhancement is beneficial to the subsequent image processing, but it is easy to introduce discrete noise. The discrete noise can be removed by morphological opening operation of corrosion and then expansion. The grayscale change gradient of adjacent pixels in the first direction and the second direction is calculated, and the edge where the pixel with the largest grayscale change gradient is located is selected as the boundary of the white display area. The vertex coordinates of the white display area can be calculated according to the boundary of the white display area, and the center point coordinates of the white display area are further used as the coordinates of the feature points. Based on the assumption that the central area is undistorted, the coordinates of the 6×6 feature points in the central area of ​​the shooting picture are selected, and the rotation angle and scaling scale of the shooting picture relative to the standard calibration pattern are calculated. The shooting picture is adjusted according to the rotation angle and scaling scale to obtain a corrected picture. In order to avoid excessive errors in the extraction of feature point coordinates in the peripheral area, the central area of ​​the correction image is filled with the image phase to form a correction pattern with the same size as the standard pattern. The correction pattern and the standard correction pattern are then aligned according to the central area, and the offset of each feature point outside the central area is counted. In order to improve the calculation accuracy of the offset, the above steps are repeated for iterative operation. When the number of iterations exceeds the set maximum value T or the maximum offset of the corresponding key point is less than the threshold σ, the iteration is stopped. The original texture image displayed on the display device is stretched, shrunk and affine transformed according to the offset using a graphics rendering interface, and then remapped to the display area of ​​the corresponding display device to achieve actual display image correction.

[0087] The embodiment of the present invention further provides a display device, including a display device and a distorted image correction device, wherein the distorted image correction device pre-stores the offset of each feature point obtained by the above-mentioned distorted image correction method, and the distorted image correction device is used to correct the display image output by the display device according to the offset. Since the display device in the embodiment of the present invention can execute the distorted image correction method provided in the above-mentioned embodiment, it has the same or corresponding technical effect.

[0088] Optionally, the display device includes a wearable display device based on silicon-based display, such as a VR or AR display device.

[0089] Note that the above are only preferred embodiments of the present invention and the technical principles used. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and that various obvious changes, readjustments, combinations and substitutions can be made by those skilled in the art without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments, and may include more other equivalent embodiments without departing from the concept of the present invention, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for correcting a distorted image, characterized in that: include: S1, obtaining a photographic image of a standard calibration pattern displayed on a display device; S2, preprocessing the captured image to extract coordinates of feature points in the captured image; S3, selecting a preset number of feature points in the central area of ​​the captured image, and adjusting the rotation and scale of the captured image according to the selected feature points to obtain a corrected image; S4, calculating, according to the correction picture and the standard correction pattern, the offset of each feature point of the correction picture relative to the corresponding position of the standard correction pattern; Calculating the offset of each feature point in the standard calibration pattern according to the correction picture and the standard calibration pattern includes: Filling the central area of ​​the correction image to form a correction pattern with the same size as the standard correction pattern; Aligning the calibration pattern and the standard calibration pattern according to the central area, and counting the offset of each feature point outside the central area; S5. Correct the actual display image of the display device according to the offset.

2. The method for correcting distorted images according to claim 1, characterized in that: Also includes: S1 to S4 are executed in a loop until a loop termination condition is reached; the loop termination condition includes that the number of loops exceeds a preset maximum value or the maximum offset of the feature point is less than a preset threshold value.

3. The method for correcting distorted images according to claim 1, wherein: Acquiring a photographed picture of a standard calibration pattern displayed by a display device includes: Fixing the display device on a fixture table; Controlling the display device to display a standard calibration pattern; The shooting camera is fixed at the position of the fixture slot, and the standard calibration pattern is photographed and stored to obtain the shooting picture.

4. The method for correcting distorted images according to claim 1, wherein: The standard calibration pattern includes a plurality of white display areas arranged in an array; Preprocessing the captured image to extract coordinates of feature points in the captured image includes: Performing contrast enhancement on the captured image and removing discrete noise points by using morphological opening operation; Calculating the grayscale change gradients of adjacent pixels in a first direction and a second direction, and selecting the side where the pixel with the largest grayscale change gradient is located as the boundary of the white display area; Taking the coordinates of the center point of the white display area as the coordinates of the feature point; The first direction is parallel to the row direction of the array formed by the white display areas, and the second direction is parallel to the column direction of the array formed by the white display areas.

5. The method for correcting distorted images according to claim 4, characterized in that: The shape of the white display area includes rectangle, circle or triangle.

6. The method for correcting distorted images according to claim 1, wherein: Before preprocessing the captured image, the method further includes: The shooting camera performs distortion correction on the captured image.

7. The method for correcting distorted images according to claim 1, wherein: Selecting a preset number of feature points in the central area of ​​the captured image, and adjusting the rotation and scale of the captured image according to the selected feature points to obtain a corrected image, including: Selecting 6×6 feature point coordinates in the central area of ​​the photographed image, and calculating a rotation angle and a scaling scale of the photographed image relative to the standard calibration pattern; The captured image is adjusted according to the rotation angle and the zoom scale to obtain the corrected image.

8. The method for correcting distorted images according to claim 1, wherein: According to the offset, correcting the actual display image of the display device includes: The original texture image displayed by the display device is stretched, shrunk and affine transformed according to the offset using a graphics rendering interface, and then remapped to a display area corresponding to the display device to achieve actual display image correction.

9. A display device, characterized in that: It comprises a display device and a distorted image correction device, wherein the distorted image correction device pre-stores the offset of each feature point obtained by the distorted image correction method described in any one of claims 1 to 8, and the distorted image correction device is used to correct the display image output by the display device according to the offset.

10. The display device according to claim 9, characterized in that The display device includes a wearable display device based on a silicon-based display.

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