Graphical distortion measurement method and calibration method for virtual reality display devices

Abstract

This application relates to the field of virtual reality technology, and discloses a method for measuring graphic distortion and a calibration method for a virtual reality display device. The measurement method includes the following steps: obtaining a virtual reality imaging image of an image source, where the image source includes a plurality of test graphics; respectively calculating the distortion values of the images corresponding to the respective test graphics in the virtual reality imaging image; and taking the maximum value among the respective distortion values as the graphic distortion amount of the virtual reality display device. In the above solution, by calculating the graphic distortion amount of the image source and performing pre-distortion correction on the image source when the distortion amount is greater than the distortion threshold, the image projected onto the display after pre-distortion correction of the image source is a normal image, overcoming the problem of image distortion that occurs when the image source is directly projected onto the display without pre-distortion correction.

Description

Technical Field

[0001] This application generally relates to the field of virtual reality, and in particular, to a method for measuring graphic distortion and a calibration method for a virtual reality display device. Background Art

[0002] In a virtual reality system, in order to enable users to have a real immersive experience visually, a virtual reality device needs to cover the visual range of the human eye as much as possible. Therefore, a specific spherical arc lens needs to be installed in the virtual reality device. However, when a traditional image is projected into the human eye using a curved lens, the image is distorted and has aberrations. Image aberration refers to the deformation such as extrusion, stretching, offset, and distortion of the geometric positions of the image pixels during the imaging process, which changes the geometric position, size, shape, orientation, etc. of the image. Therefore, the human eye cannot obtain the positioning in the virtual space, that is, the images around the user in the virtual reality are all distorted. Summary of the Invention

[0003] This application expects to provide a method for measuring graphic distortion and a calibration method for a virtual reality display device to solve the problem of graphic aberration existing in virtual reality devices.

[0004] This application on the one hand provides a method for measuring graphic distortion of a virtual reality display device, including the following steps:

[0005] Obtain the virtual reality imaging image of the image source, where the image source includes a plurality of test patterns;

[0006] Calculate the distortion values of the images corresponding to each of the test patterns in the virtual reality imaging image respectively;

[0007] Take the maximum value among the distortion values as the graphic distortion amount of the virtual reality display device.

[0008] Further, calculate the distortion value of each test pattern according to the distance between specific points in the image corresponding to the test pattern in each virtual reality imaging image.

[0009] Further, the image source is a plurality of monochromatic test patterns set on a pure color background. The plurality of test patterns include a first rectangle, and a second rectangle is set at each of the four corners and the center position of the first rectangle. The boundary widths of the first rectangle and the second rectangle are both one pixel. Calculate the distortion value in the width direction and the distortion value in the height direction of each test pattern according to the pixel coordinates of the specific points of each test pattern.

[0010] Further, calculate the distortion value of each test pattern according to the following relational expression:

[0011]

[0012]

[0013] Among them, D W is the distortion value in the width direction, D H is the distortion value in the height direction, W1 is the distance between the bottom-end pixels in the width direction, W2 is the distance between the top-end pixels in the width direction, W3 is the distance between the pixels at the point with the maximum distortion in the width direction, H1 is the distance between the left-end pixels in the height direction, H2 is the distance between the right-end pixels in the height direction, and H3 is the distance between the pixels at the point with the maximum distortion in the height direction.

[0014] On the other hand, the present application provides a method for measuring the graphic distortion of a virtual reality display device, including the following steps:

[0015] Successively obtain the virtual reality imaging images of multiple different image sources, and each of the image sources includes a specific test pattern;

[0016] Calculate the distortion values of the images corresponding to the test patterns in each virtual reality imaging image respectively;

[0017] Take the maximum value among the distortion values as the graphic distortion amount of the virtual reality display device.

[0018] Furthermore, the image source is the monochromatic test pattern set on a solid-color background, at least one of the image sources has the test pattern as a first rectangle, and at least five of the image sources have the test pattern as a second rectangle;

[0019] In the state where each of the image sources overlaps, each of the second rectangles is located at the four corners and the center position of the first rectangle, and the boundary widths of the first rectangle and the second rectangle are both one pixel;

[0020] Calculate the distortion values of each of the test patterns according to the following relational expressions:

[0021]

[0022]

[0023] Among them, D W is the distortion value in the width direction, D H is the distortion value in the height direction, W1 is the distance between the bottom-end pixels in the width direction, W2 is the distance between the top-end pixels in the width direction, W3 is the distance between the pixels at the point with the maximum distortion in the width direction, H1 is the distance between the left-end pixels in the height direction, H2 is the distance between the right-end pixels in the height direction, and H3 is the distance between the pixels at the point with the maximum distortion in the height direction.

[0024] Further, the image source is the monochromatic test pattern set on a solid - color background. The test pattern is multiple straight lines with a width of one pixel arranged in parallel at equal intervals. The intervals between the straight lines in different image sources are the same, and the inclination angles are different;

[0025] Obtain the brightness curve at a predetermined position. The predetermined position is the position in the virtual - reality imaging image corresponding to the intercepting line perpendicular to the straight line;

[0026] Calculate the distance between adjacent wave - peak values in the brightness curve;

[0027] Calculate the distortion value of each predetermined position of the test pattern according to the following relational formula:

[0028]

[0029] where D is the distortion value, W i is the distance between adjacent wave - peak values in the brightness curve, i and n are both natural numbers, and n is the number of intervals where the intercepting line intersects the straight line.

[0030] On the other hand, the present application provides a method for calibrating graphic distortion of a virtual - reality display device, including the following steps:

[0031] Adopt the method for measuring graphic distortion of the virtual - reality display device described above to obtain the graphic distortion amount;

[0032] Judge whether the graphic distortion amount is greater than the distortion threshold. If so, calibrate the distortion of the image source according to the following relational formula:

[0033]

[0034] where k1 is the distortion - correction parameter; (x, y) is the pixel point of the image after pre - distortion; (x0, y0) is the pixel point in the image source, r = x 2 +y 2 , x max is the maximum value in the x - coordinate direction, and y max is the maximum value in the y - coordinate direction.

[0035] Further, perform the compensation calculation for distortion calibration through the bilinear interpolation algorithm, and determine the weights of the four pixel points around (x1, y1) in the bilinear interpolation compensation calculation through the following weight relational formula, and use the pixel point with the largest weight as the pixel point of the image after pre - distortion:

[0036]

[0037] Among them, x0 and y0 are floating-point numbers, and (x1, y1) are the coordinate values of the upper-left corner point obtained by rounding down the pixel point (x0, y0) in the image source, and W lt is the weight of the upper-left pixel of (x1, y1), and W lb is the weight of the upper-right pixel of (x1, y1), and W rt is the weight of the lower-left pixel of (x1, y1), and W rb is the weight of the lower-right pixel of (x1, y1).

[0038] Further, after performing distortion calibration on the image source, repeatedly obtain the graphic distortion amount of the virtual reality imaging image of the distortion-calibrated image source, and determine again whether the re-obtained graphic distortion amount is greater than the distortion threshold. If so, perform distortion calibration on the distortion-calibrated image source again until the graphic distortion amount of the virtual reality imaging image of the image source after the second distortion calibration is less than the distortion threshold.

[0039] The above solution provided by this application calculates the graphic distortion amount of the image source, and when the distortion amount is greater than the distortion threshold, performs pre-distortion correction on the image source, so that the image source after pre-distortion correction is a normal image when projected onto the display, overcoming the problem of image distortion that occurs when the image source is directly projected onto the display without pre-distortion correction. Description of the Drawings

[0040] By reading the following detailed description of the non-restrictive embodiments with reference to the accompanying drawings, other features, objects, and advantages of this application will become more obvious:

[0041] Figure 1 is the flowchart of the method for measuring graphic distortion of a virtual reality display device provided by an embodiment of the present invention;

[0042] Figure 2 is the schematic diagram of a signal source;

[0043] Figure 3 is the schematic diagram of the structural relationship of pincushion distortion;

[0044] Figure 4 is the schematic diagram of the structural relationship of barrel distortion;

[0045] Figure 5 is the flowchart of the method for measuring graphic distortion of a virtual reality display device provided by another embodiment of the present invention;

[0046] Figure 6 is the schematic diagram of a horizontal straight line image source;

[0047] Figure 7 is the schematic diagram of a vertical straight line image source;

[0048] Figure 8Schematic diagram of a 45° inclined straight-line image source;

[0049] Figure 9 Schematic diagram of a -45° inclined straight-line image source;

[0050] Figure 10 Schematic diagram of intercepting a horizontal straight-line image source;

[0051] Figure 11 Schematic diagram of the brightness curve at one of the intercepting positions;

[0052] Figure 12 Flowchart of the graphic distortion calibration method for a virtual reality display device provided by another embodiment of the present invention. Detailed implementation manners

[0053] The present application will be further described in detail below with reference to the accompanying drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the related invention and are not intended to limit the invention. Additionally, it should be noted that for the convenience of description, only the parts related to the invention are shown in the drawings.

[0054] It should be noted that, without conflict, the embodiments in the present application and the features in the embodiments can be combined with each other. The present application will be described in detail below with reference to the drawings and embodiments.

[0055] As Figure 1 shown, the graphic distortion measurement method for a virtual reality display device provided by an embodiment of the present invention includes the following steps:

[0056] S1: Obtain the virtual reality imaging image of the image source, where the image source includes a plurality of test patterns;

[0057] Through a camera-type CCD (Charge-Coupled Device) facing the lens of the virtual reality display device, obtain the virtual reality imaging image formed by the projection of the image source on the display. Generally, the obtained virtual reality imaging image is the image within the entire field of view angle. Of course, it can also be the image within less than the entire field of view angle. Obtaining the image within the entire field of view angle can fully display the distortion of the image on the display, which is beneficial for subsequent calibration of the distortion.

[0058] S2: Calculate the distortion values of the images corresponding to each of the test patterns in the virtual reality imaging image respectively;

[0059] A plurality of test patterns can be evenly spaced in the image source. Preferably, the plurality of test patterns cover the entire field of view angle to fully display the distortion of the image on the display, and calculate the distortion values of the images corresponding to each test pattern respectively.

[0060] S3: Use the maximum value among the distortion values as the graphic distortion amount of the virtual reality display device.

[0061] Using the maximum value among the distortion values as the graphic distortion amount of the virtual reality display device is to facilitate determining whether image calibration is required in subsequent distortion calibration. If the graphic distortion amount as the maximum value can be accepted, then image calibration may no longer be needed.

[0062] Further, calculate the distortion value of each test pattern according to the distance between the specific points in the image corresponding to the test pattern in each virtual reality imaging image.

[0063] Generally, regular patterns are used as test patterns, such as but not limited to rectangles, squares, hexagons, etc. The specific points in the image can generally be vertices, the points with the maximum distortion, etc. The distortion value of each test pattern can be determined by the horizontal distance and vertical distance of the specific points in the image.

[0064] Further, as Figure 2 shown, the image source is multiple monochromatic test patterns set on a solid-color background. The multiple test patterns include a first rectangle, and second rectangles are set at the four corners and the center position of the first rectangle. The boundary widths of the first rectangle and the second rectangles are both one pixel. Calculate the distortion value in the width direction and the distortion value in the height direction of each test pattern according to the pixel coordinates of the specific points of each test pattern.

[0065] For example, the width of the first rectangle is W, the height is H, the width of the second rectangle is W / 4, and the height is H / 4.

[0066] Using an image source with a solid-color background and monochromatic test patterns facilitates screening out the test patterns. By establishing a coordinate system in the virtual reality imaging image, determine the pixel coordinates of the screened-out test patterns.

[0067] To improve the accuracy of test pattern screening, two colors with high contrast are selected for the background and the test patterns. For example but not limited to, the background is selected as black and the test patterns are selected as white. In this case, obtain the full-image brightness information of the virtual reality imaging image. The brightness value of the background is 0, and the brightness value of the test patterns is 255. Screen out the pixel points with a brightness value of 255, which are the images corresponding to the test patterns. According to the coordinate system established in the virtual reality imaging image, determine each pixel coordinate.

[0068] In addition, the boundary widths of the first rectangle and the second rectangles are both one pixel, which can improve the accuracy of the screened-out pixels and ensure the accuracy of the calculated distortion value.

[0069] Further, as Figure 3 、 Figure 4As shown, the distortion value of each of the test patterns is calculated according to the following relationship:

[0070]

[0071]

[0072] where D W is the distortion value in the width direction, D H is the distortion value in the height direction, W1 is the distance between the bottom-end pixels in the width direction, W2 is the distance between the top-end pixels in the width direction, W3 is the distance between the pixels at the point of maximum distortion in the width direction, H1 is the distance between the left-end pixels in the height direction, H2 is the distance between the right-end pixels in the height direction, and H3 is the distance between the pixels at the point of maximum distortion in the height direction.

[0073] Further, as Figure 5 shown, another aspect of the present application provides a method for measuring the graphic distortion of a virtual reality display device, including the following steps:

[0074] S10: Sequentially obtain the virtual reality imaging images of multiple different image sources, and each of the image sources includes a specific test pattern;

[0075] The virtual reality imaging images formed by projecting multiple different image sources onto the display are sequentially obtained through a camera-type CCD (Charge-Coupled Device) facing the lens of the virtual reality display device. The display may be a head-mounted display.

[0076] The test patterns in different image sources are different. The difference in the test patterns mentioned here can be at least any one of shape, size, and position.

[0077] S20: Calculate the distortion values of the images corresponding to the test patterns in each of the virtual reality imaging images respectively;

[0078] S30: Take the maximum value among the distortion values as the graphic distortion amount of the virtual reality display device.

[0079] Further, the image source is a monochromatic test pattern provided on a solid-color background. There is at least one image source with the test pattern being a first rectangle, and at least five image sources with the test pattern being a second rectangle;

[0080] In the state where the image sources overlap, each of the second rectangles is located at the four corners and the center position of the first rectangle, and the boundary widths of the first rectangle and the second rectangle are both one pixel; for the state after the image sources overlap, reference can be made to Figure 2 .

[0081] Calculate the distortion values of the test patterns according to the following relationship:

[0082]

[0083]

[0084] where D W is the distortion value in the width direction, D H is the distortion value in the height direction, W1 is the distance between the bottom-end pixels in the width direction, W2 is the distance between the top-end pixels in the width direction, W3 is the distance between the pixels at the point of maximum distortion in the width direction, H1 is the distance between the left-end pixels in the height direction, H2 is the distance between the right-end pixels in the height direction, and H3 is the distance between the pixels at the point of maximum distortion in the height direction.

[0085] Adopt an image source with a solid-color background and a monochromatic test pattern, which is convenient for screening out the test pattern. By establishing a coordinate system in the virtual reality imaging image, determine the pixel coordinates of the selected test pattern.

[0086] To improve the accuracy of test pattern screening, two colors with high contrast are selected for the background and the test pattern. For example, but not limited to, the background is selected as black and the test pattern is selected as white. In this case, obtain the full-image brightness information of the virtual reality imaging image. The brightness value of the background is 0, and the brightness value of the test pattern is 255. Screen out the pixel points with a brightness value of 255, which are the images corresponding to the test pattern. According to the coordinate system established in the virtual reality imaging image, determine the pixel coordinates.

[0087] In addition, the boundary widths of the first rectangle and the second rectangle are both one pixel, which can improve the accuracy of the selected pixels and ensure the accuracy of the calculated distortion values.

[0088] Furthermore, the image source is the monochromatic test pattern set on a solid-color background, and the test pattern is multiple straight lines with a width of one pixel arranged in parallel at equal intervals. The intervals between the straight lines in different image sources are the same and the inclination angles are different;

[0089] For example, but not limited to, as Figures 6-9 shown, there are four image sources. The image sources are all black backgrounds with white straight lines. The straight lines in the four image sources are horizontal straight lines, vertical straight lines, 45° inclined straight lines, and -45° inclined straight lines respectively. For example, in one image source, 5-20 rows of straight lines are arranged horizontally at equal intervals, in another image source, vertical straight lines are evenly distributed from the middle to both sides at the same interval, in one image source, straight lines with a 45° inclination angle are evenly distributed at the same interval, and in another image source, straight lines with a -45° inclination angle are evenly distributed at the same interval.

[0090] A black background and a white straight line with a width of one pixel can also be used here to improve the accuracy of calculation.

[0091] Obtain the brightness curve at a predetermined position, where the predetermined position is the position in the virtual reality imaging image corresponding to the intercepting line perpendicular to the straight line;

[0092] Interception can be performed at any predetermined position or regular predetermined positions. For example, Figure 10 As shown, taking the image source of a horizontal straight line as an example, interception can be performed at 1 / 8H, 2 / 8H, 4 / 8H, 6 / 8H, 7 / 8. Generally, the distortion amount at the center is smaller than that at the edge. Using the above regular interception positions, while meeting the calculation accuracy, the calculation amount is also reduced and the calculation speed is improved.

[0093] Obtain the brightness curve as shown Figure 11 at each interception position. The distance between every two adjacent wave peaks in this brightness curve is the distance between the corresponding two straight lines at the interception position.

[0094] Calculate the distances between adjacent wave peaks in the brightness curve;

[0095] Calculate the distortion values at each predetermined position of the test pattern according to the following relational expression:

[0096]

[0097] where D is the distortion value, W i is the distance between adjacent wave peaks in the brightness curve, and both i and n are natural numbers, and n is the number of intervals where the intercepting line intersects the straight line.

[0098] Another aspect of the present application provides a method for calibrating graphic distortion of a virtual reality display device, including the following steps:

[0099] S31: Adopt the method for measuring graphic distortion of the virtual reality display device described above to obtain the graphic distortion amount;

[0100] S32: Determine whether the graphic distortion amount is greater than a distortion threshold, where the distortion threshold is used to represent the maximum acceptable distortion amount. If so, perform distortion calibration on the image source according to the following relational expression:

[0101]

[0102] where k1 is a distortion correction parameter; (x, y) is the pixel point of the image after pre-distortion; (x0, y0) is the pixel point in the image source, r = x 2 +y 2 , x max is the maximum value in the x coordinate direction, ymax is the maximum value in the y - coordinate direction.

[0103] Among them, when performing distortion calibration, the entire image source can be calibrated, or only the area with large distortion positions can be calibrated. Calibrating the entire image source can improve accuracy, and calibrating only the area with large distortion positions can reduce the computational amount and improve the calculation speed.

[0104] In the above - mentioned solution, by calculating the graphic distortion amount of the image source and, when the distortion amount is greater than the distortion threshold, performing pre - distortion correction on the image source, and then the pre - distorted image is further processed by the optical system of the virtual reality display device to eliminate distortion. That is, the image source after pre - distortion correction is projected onto the display to obtain a normal image, overcoming the problem of image distortion that occurs when the image source is directly projected onto the display without pre - distortion correction.

[0105] Furthermore, through the bilinear interpolation algorithm for compensating calculation of distortion calibration, and determining the weights of the four pixel points around (x1, y1) in the bilinear interpolation compensation calculation through the following weight relationship formula, and taking the pixel point with the largest weight as the pixel point of the pre - distorted image:

[0106]

[0107] where x0 and y0 are floating - point numbers, (x1, y1) is the coordinate value of the upper - left corner point obtained by rounding down the pixel point (x0, y0) in the image source, W lt is the weight of the upper - left pixel of (x1, y1), W lb is the weight of the upper - right pixel of (x1, y1), W rt is the weight of the lower - left pixel of (x1, y1), W rb is the weight of the lower - right pixel of (x1, y1).

[0108] Since x0 and y0 obtained by the bilinear interpolation algorithm are floating - point numbers, while the pixel points of the pre - distorted image should be natural numbers. Through the above - mentioned weight calculation, the pixel point with the largest weight among the four pixel points around (x1, y1) is taken as the pixel point of the pre - distorted image, realizing that the coordinates of the pixel points of the pre - distorted image are natural numbers.

[0109] Furthermore, after calibrating the distortion of the image source, repeatedly obtain the graphic distortion amount of the virtual reality imaging image of the image source after distortion calibration, and then determine again whether the newly obtained graphic distortion amount is greater than the distortion threshold. If so, perform distortion calibration on the image source after distortion calibration again until the graphic distortion amount of the virtual reality imaging image of the image source after the second distortion calibration is less than the distortion threshold.

[0110] After one distortion calibration, there may be an incomplete calibration. To ensure that the images output by the virtual reality display device are accurate to the greatest extent, multiple graphic distortion calibrations can be performed according to the above method until the graphic distortion amount of the virtual reality imaging image of the image source after distortion calibration is less than the distortion threshold.

[0111] The above description is only the preferred embodiment of the present application and the description of the applied technical principles. Those skilled in the art should understand that the scope of the invention involved in the present application is not limited to the technical solutions formed by the specific combination of the above technical features, and should also cover other technical solutions formed by any combination of the above technical features or their equivalent features without departing from the inventive concept. For example, the technical solutions formed by the mutual replacement of the above features and the technical features (but not limited to) with similar functions disclosed in the present application.

Claims

1. A method for measuring graphic distortion of a virtual reality display device, characterized in that, Including the following steps: Obtain the virtual reality imaging image of the image source, where the image source includes a plurality of test patterns; Calculate the distortion values of the images corresponding to each of the test patterns in the virtual reality imaging image respectively; Take the maximum value among the distortion values as the graphic distortion amount of the virtual reality display device; Calculate the distortion values of each test pattern according to the distances of specific points in the images corresponding to the test patterns in each virtual reality imaging image; The image source is a plurality of monochromatic test patterns set on a solid color background. The plurality of test patterns include a first rectangle, and second rectangles are arranged at the four corners and the center position of the first rectangle. The boundary widths of the first rectangle and the second rectangles are both one pixel. Calculate the distortion values in the width direction and the height direction of each test pattern according to the pixel coordinates of the specific points of each test pattern.

2. The method for measuring graphic distortion of a virtual reality display device according to claim 1, wherein Calculate the distortion values of each test pattern according to the following relational expression: ； ； Among them, D W is the distortion value in the width direction, D H is the distortion value in the height direction, W 1 is the distance between the bottom-end pixels in the width direction, W 2 is the distance between the top-end pixels in the width direction, W 3 is the distance between the pixels at the point of maximum distortion in the width direction, H 1 is the distance between the left-end pixels in the height direction, H 2 is the distance between the right-end pixels in the height direction, H 3 is the distance between the pixels at the point of maximum distortion in the height direction.

3. A method for measuring graphic distortion of a virtual reality display device, characterized in that, Including the following steps: Sequentially obtain the virtual reality imaging images of a plurality of different image sources, and each image source includes specific test patterns; Calculate the distortion values of the images corresponding to the test patterns in each virtual reality imaging image respectively; Take the maximum value among the distortion values as the graphic distortion amount of the virtual reality display device; The image source is a monochromatic test pattern set on a solid color background. There is at least one image source with the test pattern being a first rectangle, and at least five image sources with the test pattern being a second rectangle; In the state where the image sources overlap, each second rectangle is located at the four corners and the center position of the first rectangle respectively. The boundary widths of the first rectangle and the second rectangles are both one pixel.

4. The method for measuring the graphic distortion of a virtual reality display device according to claim 3, characterized in that Calculate the distortion values of each test pattern according to the following relational expression: ； ； Among them, D W is the distortion value in the width direction, D H is the distortion value in the height direction, W 1 is the distance between the bottom-end pixels in the width direction, W 2 is the distance between the top-end pixels in the width direction, W 3 is the distance between the pixels at the point of maximum distortion in the width direction, H 1 is the distance between the left-end pixels in the height direction, H 2 is the distance between the right-end pixels in the height direction, H 3 is the distance between the pixels at the point of maximum distortion in the height direction.

5. The method for measuring the graphic distortion of a virtual reality display device according to claim 4, characterized in that, The image source is a monochromatic test pattern set on a solid color background. The test pattern is a plurality of straight lines with a width of one pixel arranged in parallel at equal intervals. The intervals between the straight lines in different image sources are the same and the inclination angles are different; Obtain the brightness curve at a predetermined position, where the predetermined position is the position corresponding to the intercepting line perpendicular to the straight line in the virtual reality imaging image; Calculate the distances between adjacent peak values in the brightness curve; Calculate the distortion values of each predetermined position of the test pattern according to the following relational expression: Among them, D is the distortion value, W i is the distance between adjacent wave peaks in the brightness curve, i, n are all natural numbers, n is the number of intervals where the intercepting line intersects the straight line.

6. A method for calibrating graphic distortion of a virtual reality display device, characterized in that, Including the following steps: Adopt the method for measuring the graphic distortion of a virtual reality display device according to any one of claims 1-5 to obtain the graphic distortion amount; Judge whether the graphic distortion amount is greater than the distortion threshold. If so, perform distortion calibration on the image source according to the following relational expression: ； Among them, are distortion correction parameters; are the pixel points of the image after pre-distortion; are the pixel points in the image source, , , is x the maximum value in the coordinate direction, y is the maximum value in the 7. The method for calibrating graphic distortion of a virtual reality display device according to claim 6, wherein Perform compensation calculations for distortion calibration through the bilinear interpolation algorithm, and determine through the following weight relationship The weights of the four pixel points around in the bilinear interpolation compensation calculation, and use the pixel point with the largest weight as the pixel point of the pre-distorted image: ； Among them, , are floating-point numbers, is the coordinate value of the upper-left corner point obtained by rounding down the pixel point in the image source, is the weight of the upper-left pixel, is the weight of the upper-right pixel, is the weight of the lower-left pixel, is the weight of the lower-right pixel.

8. The method for calibrating graphic distortion of a virtual reality display device according to claim 6 or 7, characterized in that After performing distortion calibration on the image source, repeat to obtain the graphic distortion amount of the virtual reality imaging image of the image source after distortion calibration, and judge again whether the newly obtained graphic distortion amount is greater than the distortion threshold. If so, perform distortion calibration on the image source after distortion calibration again until the graphic distortion amount of the virtual reality imaging image of the image source after the second distortion calibration is less than the distortion threshold.

Images