Active off-axis angle correction for image-based illumination

Abstract

An image rendered on a display is corrected for a target, including: an object tracking device that measures a relative position to the target; a configuration file comprising at least a list of target angles for rotating the display with respect to a relative position of the object tracking device; a measurement control system that captures a profile, the measurement control system initiating a sequence by tracking a stability display while displaying a gradation value of the target as a basis for a subsequent angle measurement result; and an angle measurement rotation device, the angle measurement rotation device comprising a pair of servo motors for placing a rotation point on an axis alignment surface normal of the display.

Description

Technical Field

[0001] The present disclosure relates to correcting display technology brightness and color uniformity. Specifically, when the display is used as a light source to illuminate a subject, or when the display is directly photographed from different angles, calibrating and dynamically correcting the imaging deviation of the display. Background Art

[0002] Current lighting fixtures and direct display devices that employ various wavelength light emitting diodes (LEDs) face significant challenges, including noticeable chromaticity shifts and brightness attenuation when light propagates off-axis from the LED's orientation. These off-axis deviations result in noticeable and undesirable changes in the color quality of the emitted light as perceived by an observer or when it illuminates a subject. Such chromaticity deviations not only affect visual consistency and aesthetic appeal, but also affect the functional effectiveness of these devices in applications where accurate color representation is critical and preserving creative intent is a major priority. Traditional approaches to addressing the above issues include providing a maximum angular range of acceptable viewing and beam angles or emission angles. Thus, there is a need for methods and systems that can address the problem of imaging deviations when illuminating a subject outside of the optimal emission angle or when capturing a display from an off-axis angle. Summary of the invention

[0003] The present disclosure implements techniques for calibrating and dynamically correcting imaging aberrations of a display when the display is used as a light source to illuminate a subject, or when the display is photographed directly from different angles.

[0004] In one implementation, a system for correcting an image rendered on a display for a target is disclosed. The system includes an object tracking device that measures a relative position to a target, a configuration file that includes at least a list of target angles for rotating the display relative to the relative position of the object tracking device, a measurement control system that ingests the configuration file, the measurement control system initiates a sequence by tracking a stability display while displaying grayscale values ​​of the target that serve as a basis for subsequent angle measurements, and an angular rotation device that includes a pair of servo motors for placing a rotation point on an axis-aligned surface normal of the display.

[0005] In another implementation, a method for applying correction to an image rendered on a display is disclosed. The method includes: receiving calibration data including a brightness correction lookup table; receiving target color space primaries and a white point from pole locations, wherein the pole locations are located at poles of a hemisphere formed above the display; calculating a normalized primary color matrix including tristimulus values ​​using the target color space primaries and the white point; calculating chromaticity correction using the normalized primary color matrix; and calculating brightness correction using RGB values ​​of the display and the brightness correction lookup table.

[0006] Other features and advantages should be apparent from this description, which illustrates by way of example various aspects of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0007] The details of the present disclosure, both as to its structure and operation, may be gleaned in part by studying the accompanying drawings, in which like reference numerals refer to like parts, and in which:

[0008] Figure 1A is a block diagram of a correction system according to one implementation of the present disclosure;

[0009] Figure 1B is a pictorial depiction of a correction system according to one implementation of the present disclosure;

[0010] Figure 2 is a flow chart of a correction process according to one implementation of the present disclosure;

[0011] Figure 3 shows an example of ΔE ITP error for a sample hemisphere according to one implementation of the present disclosure;

[0012] Figure 4 shows real-world off-axis color-correlated temperature measurements of a device according to one implementation of the present disclosure, where the plane at 6504 Kelvin represents the correction target;

[0013] Figure 5 shows the RGB correction ratios required to correct a device shifted to cyan off-axis according to one implementation of the present disclosure;

[0014] Figure 6 shows normalized brightness values ​​before and after correction according to one implementation of the present disclosure;

[0015] Figure 7 is a flow chart of a detailed view of a correction process according to one implementation of the present disclosure. DETAILED DESCRIPTION

[0016] As described above, current lighting fixtures and direct display devices that employ various wavelength LEDs in a repeating pattern face significant challenges, including noticeable chromaticity shifts and brightness falloff when light propagates off-axis from the LED's orientation. These off-axis deviations result in noticeable and undesirable changes in the color quality of the emitted light as perceived by the target or when it illuminates a subject. Such chromaticity changes not only affect visual consistency and aesthetic appeal, but also affect the functional effectiveness of these devices in applications where accurate color representation is critical and preserving creative intent is a major priority. The above-mentioned off-axis deviations may include chromaticity errors (or color errors) and / or brightness errors (or brightness errors), which may be caused by several different factors including geometry and optics.

[0017] For example, geometric factors include the spatial separation of red, green, and blue (RGB) LEDs. In an RGB LED package, the red, green, and blue LEDs are spatially separated. When viewed off-axis, the distance that the light emitted by each LED travels to the target changes and affects the color mixing. As the angle increases, the target sees less of the LED emitting surface, which contributes to a decrease in perceived brightness. In extreme cases, the LED package may self-occlude sub-pixels, which can present significant brightness loss or color mixing issues. Geometric factors can also include geometric effects related to the projected area of ​​the light source seen by the observer. That is, the perceived brightness of a light source decreases with the cosine of the angle between the observer's line of sight and the normal to the light source (cosine law).

[0018] In another example, optical factors include the optical design of the LED package (including lenses or encapsulants) being optimized for on-axis viewing. Therefore, when viewed off-axis, the components of the package may cause more light scattering or absorption, resulting in reduced brightness. Optical factors can also include wavelength-dependent refraction. That is, when light passes through a material such as an LED lens or any protective covering, different wavelengths of light (i.e., different colors) are refracted differently. Therefore, refraction may cause different colors to diffuse or focus differently, thereby changing the color balance perceived at different angles.

[0019] To address the above-mentioned deviation problem, an implementation of the present disclosure provides an active off-axis color correction system that receives the position of a target and applies correction to a rendered image. In one implementation, methods and systems for lighting and display technologies for dynamically correcting off-axis brightness and color errors are disclosed. For example, when a display is used as a light source to illuminate a subject, or the display is photographed directly from different angles, the methods and systems can simulate and dynamically correct the imaging deviation of the display. These methods and systems can be applied to lighting and display technologies, virtual production, location-based entertainment (LBE), and the media and entertainment industries. In one implementation, imaging on a lamp or LED display is used to illuminate a target, is photographed directly, or is viewed under suboptimal conditions from a known target position.

[0020] The first function of the present disclosure is to dynamically correct chromaticity deviation when the target deviates from the optimal vertical viewing angle.

[0021] The second function of the present disclosure is to compensate for the brightness falloff of the display when the target reaches the range of the emission cone.

[0022] After reading the following description, it will become apparent how to implement the present disclosure in various implementations and applications. Although various implementations of the present disclosure will be described herein, it should be understood that these implementations are presented only as examples and not limitations. Therefore, the detailed description of various implementations should not be interpreted as limiting the scope or breadth of the present disclosure.

[0023] Features provided in various implementations may include, but are not limited to, one or more of the following:

[0024] (a) Measure and simulate the chromaticity and brightness errors of LED light sources from the surface normal to any point on the display hemisphere;

[0025] (b) Packing the chrominance and brightness correction models into a two-dimensional texture object for efficient sampling within the graphics pipeline;

[0026] (c) applying real-time error correction to the chromaticity of the input color value for each pixel at the LED luminaire based on the luminaire position relative to the dynamic target position; and

[0027] (d) Applying real-time error correction to the brightness of the input color value for each pixel on the LED luminaire based on the luminaire position relative to the dynamic target position.

[0028] In one implementation, the correction system includes a display, an imaging device, and additional computer hardware and software for providing image correction. The correction system can be a calibration and correction rendering system to address off-axis color shift and brightness loss. In another implementation, an active off-axis color correction system receives the current position of a target (e.g., a subject being illuminated by imaging on a display) and applies corrections to the rendered image on the display (e.g., applying corrections to ensure uniform illumination of the subject from multiple light sources and directions). The system can receive any number of subject positions and interpolate between correction zones based on a user-defined radial distance or based on the inverse square of emission attenuation. In a further implementation, the target can be a camera that captures a display, and corrections are applied to ensure not only color and brightness uniformity from different angles, but also spectral linearity of the captured image. Therefore, the correction system can be configured to address the non-uniformity faced by the media and entertainment industry when shooting display technology from a grazing angle, as well as lighting inconsistencies when using image-based lighting techniques for the subject.

[0029] Figure 1A is a block diagram of a correction system 100 according to one implementation of the present disclosure. In one implementation, the correction system 100 is a calibration system. In one implementation, the correction system 100 includes a configuration file 110, a measurement control system 120, an angle measurement rotation device 130, an image processor or input stage 136 of a device under test (DUT) 140, a rotation converter 142, a spectroradiometer 150, a buffer 152 for storing current light and control measurements, a reference measurement 160, and a database for storing data files ready for analysis.

[0030] exist Figure 1AIn the implementation shown in the diagram of , the system 100 uses absolute measurements of the wavelength and amplitude of the emitted light with corresponding horizontal and vertical viewing angles. In addition, the device under test (DUT) may be referred to as a lamp, display, or lighting device currently being calibrated, and the measurement device (MD) may be referred to as a spectroradiometer, a spectrophotometer, a tristimulus colorimeter, a photometer, or a digital camera. In addition, the reference position (RP) refers to the position where the surface normal of the DUT faces the MD and can be expressed as θ h =0° or θ h ∧θ v =0°.

[0031] exist Figure 1A In the implementation shown in the diagram of , a configuration file 110 including a list of instructions is first prepared. The configuration file 110 includes: (a) a list of each target angle for rotating the DUT relative to the fixed position spectroradiometer; (b) a list of angles classified based on optimized paths in order to reduce the travel time to each unique position; (c) relevant DUT and test condition metadata; and (d) RGB input values ​​of the DUT, including the primaries and white point at the RP.

[0032] In one implementation, the profile 110 is ingested into the measurement control system 120 where the sequence is initiated by tracking the DUT stability while displaying the target grayscale value that is the basis for subsequent angular measurements. Once the light fluctuations have stabilized, meaning that the DUT is at or near the optimal operating temperature, the calibration sequence can begin. The spectral stability of the device over time is an important metric to track because color performance may change as the temperature of the DUT increases or decreases. In one implementation, the correction system employs an initial stabilization phase to determine the optimal calibration brightness for the device and a "warm-up" duration to stabilize the device at the target grayscale value before data capture begins.

[0033] exist Figure 1A In the implementation shown in the diagram of , a high precision goniometric rotation device 130 is used to maximize the angular accuracy and automatically collect a large data set related to the angular variation of the light emission from the display / DUT 140. The goniometric rotation device 130 is equipped with two servomotors (one for rotating the base (yaw) and the other for rotating the DUT (tumble); see Figure 1B ) to precisely place the rotation point on the axis-aligned surface normal of the DUT. Assuming the rotation axis is substantially or perfectly aligned from the MD to a known location on the surface of the DUT, a gimbal with sufficient programmable logic controller (PLC) accuracy can orient the DUT along 2-DOF (degrees of freedom) to achieve a complete hemispherical data set.

[0034] exist Figure 1AIn the implementation shown in the diagram of , the reference measurement results 160 include: red, green, and blue primary color measurements at the reference position, and the ambient light control measurement results after each primary color; and the target white at the reference position and the ambient light control measurement results thereafter. Figure 1A In , the angular light measurement results include: (a) an optimized position list for sending servo motor position values ​​to both axes; (b) control messages received when the servo motors reach the target positions; (c) target RGB values ​​provided and properly formatted to the DUT's vendor-specific image processor or input stage 136; (d) a command issued to the spectroradiometer 150 to begin measurement of the target position; (e) a callback issued when the measurement is complete; (f) a black RGB value sent to the DUT for an optional ambient light control measurement; (g) a command issued to the spectroradiometer 150 to start control measurements; (h) a callback issued when the measurement is complete; (i) light and control measurements entered into buffer 152 along with the current angle value converted to a common orientation using the rotational converter 142 and a timestamp; and (j) the next position loaded. In Figure 1A In the example, database 170 includes data files ready for analysis.

[0035] In another implementation, the correction system 100 (using an existing DUT installed at the intended location) includes an object tracking system, a spectroradiometer or measurement device (MD), and a laser imaging, detection and ranging (LiDAR) device. In this implementation, the system 100 uses a "calibration in place (CIP)" method, in which an existing illumination volume including at least one of the same DUTs can be calibrated using a spectrometer and an existing object tracking system within the illumination volume. First, the position and orientation of the optical node of the MD relative to the surface of the display is determined to significantly reduce any inaccuracies that may lead to poor correction results. This approach may require additional LiDAR equipment to ensure millimeter accuracy of the DUT in a single world coordinate system. Once the geometry of the DUT is resolved relative to the optical tracking origin, the precise position and forward vector of the MD can be calculated.

[0036] In both implementations, the MDs share the same relative coordinates of the display. In one implementation, the application receives the transformation and calculates the angle between the devices in the Cartesian x / y plane. These coordinates can then be queried by an auxiliary application responsible for writing the spectral measurements to a database. In one implementation, the calibration data can then be classified. Thus, during the calibration process performed by the correction system 100, a target RGB color space can be defined based on the native primary colors and white point of the DUT from an optimal viewing angle.

[0037] Figure 1B is a graphical depiction of a correction system according to one implementation of the present disclosure. Figure 1B In the illustrated implementation of FIG. 1 , the calibration system 100 shows at least a configuration file 110 , a measurement control system 120 , an angular rotation device 130 , a DUT 140 , and a spectroradiometer 150 .

[0038] As described above, the profile 110 includes: (a) a list of each target angle for rotating the DUT 140 relative to the fixed position spectroradiometer 150; (b) a list of angles classified based on optimized paths in order to reduce travel time to each unique position; (c) relevant DUT and test condition metadata; and (d) RGB input values ​​for the DUT 140, including primaries and white point at RP. The profile 110 is then ingested into the measurement control system 120, where the sequence is initiated by tracking the stability of the DUT 140 while displaying the target grayscale value that serves as the basis for subsequent angular measurement results. Once the light fluctuations have stabilized, meaning that the DUT 140 is at or near the optimal operating temperature, the calibration sequence can begin. The spectral stability of the device over time is an important metric to track because color performance may change with increasing temperature.

[0039] exist Figure 1B In the illustrated implementation, a goniometric rotation device 130 is used to maximize angular accuracy and automatically collect a large data set related to the angular variation of light emission from the DUT 140. The goniometric rotation device 130 is equipped with two servomotors (one for rotating the base (yaw) 132 and the other for rotating the DUT (roll) 134) to precisely place the rotation point on the axis-aligned surface normal of the DUT. Assuming that the rotation axis is substantially or perfectly aligned from the MD to a known position on the surface of the DUT, a gimbal with sufficient PLC accuracy can orient the DUT along 2-DOF (degrees of freedom) to achieve a complete hemispherical data set.

[0040] Figure 2 is a flow chart of a calibration process 200 according to one implementation of the present disclosure. Figure 2 In the implementation shown in the diagram of , at step 210, the correction process 200 receives (from the calibration database) the calibration data calibrated by the correction system 100 and removes any outliers within a given threshold. At step 220, the normalized primary color matrix (MX) is calculated. In one implementation, MX is calculated by receiving the target color space primary colors and the white point from the pole position of the hemisphere (i.e., the center of the display) as follows:

[0041] (1)

[0042] MX is the normalized primary color matrix,

[0043] Wxyz is the tristimulus value of the white point,

[0044] Wy is the brightness of the white point (y component),

[0045] [] are the xyz values ​​of the red, green and blue primary colors.

[0046] Figure 3 ΔE of a sample hemisphere is shown according to one implementation of the present disclosure ITP An example of a DeltaEmpfindung ITP error. The V axis represents the vertical angle; the H axis represents the horizontal angle; the vertical axis represents ΔE ITP The point where both the horizontal and vertical angles are zero represents the center of the display.

[0047] Figure 4 The actual off-axis color-correlated temperature measurement results of a device according to one implementation of the present disclosure are shown, where the plane at 6504 Kelvin represents the correction target. The V axis represents the vertical angle; the H axis represents the horizontal angle; the vertical axis represents the correlated color temperature (CCT) in degrees Kelvin.

[0048] At step 230, a chromaticity correction ratio (CX) is calculated by transforming the XYZ tristimulus values ​​of MX from radial coordinates along the polar axis to the RGB axis as follows:

[0049] (2)

[0050] CX is the chromaticity correction ratio,

[0051] θxyz is the xyz of the polar axis.

[0052] In one implementation, at step 240, the correction ratio (CX) is applied as follows:

[0053] (3)

[0054] In one implementation, this correction is applied to the linear RGB values ​​before any brightness or encoding transformations.

[0055] In one implementation, at step 250, the correction system 100 independently calculates the brightness correction scalar (LF) and then interpolates it on the alpha channel of the correction lookup table as follows:

[0056] (4)

[0057] Brightness correction can be applied by using absolute XYZ measurements in the above method or by using normalized xyY data.

[0058] In another implementation, at step 250, correction system 100 calculates the brightness correction by fitting a polynomial at step 260. In one implementation, the polynomial is fit using a linear least squares method (LLS).

[0059] The system 100 calculates the brightness correction (lf(x)) by solving the 1-D normalized brightness correction factor as follows:

[0060] (5)

[0061] In one implementation, the calculated brightness correction is applied by clamping the amount to one half or two times, as follows:

[0062] (6)

[0063] In one implementation, the correction system 100 pre-computes brightness and chrominance corrections by fitting RGB correction ratios and brightness scaling on a Cartesian plane, and stores the data in an array with floating point precision. In another implementation, the correction system 100 stores the array of correction values ​​in an image file (e.g., by using the open source OpenEXR format) to pack the correction values ​​into an uncompressed image file. The resulting image is then packaged into a shader resource view (SRV) with the correct format (e.g., R16G16B16A16_FLOAT). Once bound, it can be sampled in the graphics application stage where the correction is applied.

[0064] In one implementation, the current corrected UV coordinates can be calculated in the vertex shader stage by comparing the target's position to the display surface coplanar unit vector as follows:

[0065] (7)

[0066] The normalized angle values ​​can then be used to look up the appropriate RGB and luminance correction ratios from the bound correction shader resource view (SRV) and apply these values ​​to the source RGB input. The chrominance and luminance correction values ​​can also be interpolated with the uncorrected values ​​using a user-defined amount of correction to apply.

[0067] Figure 5 The correction shift to cyan off-axis (see Figure 4 ) device. The V axis represents the vertical angle; the H axis represents the horizontal angle; and the vertical axis represents the RGB correction ratio.

[0068] Figure 6 Normalized brightness values ​​before and after correction according to one implementation of the present disclosure are shown.

[0069] Figure 7is a flow chart of a detailed view of a correction process 200 according to one implementation of the present disclosure.

[0070] In one specific implementation, a system for correcting an image rendered on a display for a target is disclosed. The system includes an object tracking device that measures a relative position to a target, a configuration file that includes at least a list of target angles for rotating the display relative to the relative position of the object tracking device, a measurement control system that ingests the configuration file, the measurement control system initiates a sequence by tracking a stability display while displaying grayscale values ​​of the target that serve as a basis for subsequent angle measurements, and an angular rotation device that includes a pair of servo motors for placing a rotation point on an axis-aligned surface normal of the display.

[0071] In one implementation, the object tracking device is a spectroradiometer. In one implementation, the configuration file includes a list of instructions, including: a list of angles classified based on an optimized path in order to reduce travel time to each location on the display; and a plurality of RGB input values ​​for the display. In one implementation, the plurality of RGB input values ​​include primary colors and a white point at a reference position, wherein the reference position is a position where the surface normal of the display faces the object tracking device. In one implementation, a pair of servo motors of the goniometric rotation device includes: a first servo motor for rotating a base; and a second servo motor for rotating the display to precisely place a rotation point on an axis-aligned surface normal of the display. In one implementation, the system also includes a gimbal with programmable logic controller precision to orient the display in 2-DOF, thereby achieving a hemispherical data set. In one implementation, the system also includes an image processor of the display for processing the RGB values ​​of the target. In one implementation, the system also includes a rotation converter for converting the angle values ​​to a common orientation; and a buffer for storing the converted angle values. In one implementation, the system further includes a plurality of reference measurements, including: RGB primary color measurements at a reference position; and a target white at a reference position, followed by a light control measurement. In one implementation, the light control measurement includes: an optimized position list for sending position values ​​to the yaw and roll axes of the pair of servo motors; a control message received when the pair of servo motors reach a relative position to a target; and a command issued to the object tracking device to start measuring the relative position of the target. In one implementation, the object tracking device is a laser imaging, detection, and ranging (LiDAR) device.

[0072] In another specific implementation, a method for applying correction to an image rendered on a display is disclosed. The method includes: receiving calibration data including a brightness correction lookup table; receiving target color space primaries and a white point from pole locations, wherein the pole locations are located at poles of a hemisphere formed above the display; calculating a normalized primary color matrix including tristimulus values ​​using the target color space primaries and the white point; calculating chromaticity correction using the normalized primary color matrix; and calculating brightness correction using RGB values ​​of the display and the brightness correction lookup table.

[0073] In one implementation, the method further includes removing outliers from the calibration data within a given threshold. In one implementation, the method further includes transforming the tristimulus values ​​of the normalized primary color matrix from radial coordinates to polar coordinates. In one implementation, the method further includes applying chromaticity correction to the RGB values ​​of the display. In one implementation, calculating the brightness correction includes: fitting a polynomial using a linear least squares method; and solving a 1-D normalized brightness correction factor. In one implementation, the method further includes applying the brightness correction by limiting the correction ratio of the RGB values ​​of the DUT to half or twice. In one implementation, the method further includes pre-calculating the brightness correction by fitting the correction ratio and the brightness factor on a Cartesian plane.

[0074] In order to enable those skilled in the art to implement or use the present disclosure, a description of the disclosed implementations is provided herein. Many modifications to these implementations will be apparent to those skilled in the art, and the principles defined herein may be applied to other implementations without departing from the spirit or scope of the present disclosure. Therefore, the present disclosure is not intended to be limited to the implementations shown herein, but should be given the widest scope consistent with the main and novel features disclosed herein. Thus, other variations and implementations are also possible.

[0075] One implementation includes one or more programmable processors and corresponding computer system components for storing and executing computer instructions, such as to provide calibration and correction.

[0076] Other variations and implementations are also possible. For example, in addition to entertainment applications, various implementations can also be applied to other fields, such as games, medical and life sciences, and education. In one such example, corrections can be applied to facilitate the display of medical imaging for discussion and treatment.

[0077] In a particular implementation of the present disclosure, not all features of each of the above examples are necessarily required. In addition, it should be understood that the description and drawings presented herein represent the subject matter broadly contemplated by the present disclosure. In addition, it should be understood that the scope of the present disclosure fully encompasses other implementations that may become apparent to those skilled in the art, and the scope of the present disclosure is therefore limited only by the appended claims.

Claims

1. A system for correcting an image rendered on a display for a target, the system comprising: an object tracking device that measures a relative position to a target; a configuration file, the configuration file comprising at least a list of target angles for rotating the display relative to a relative position of the object tracking device; a measurement control system that ingests the profile, the measurement control system initiating a sequence by tracking a stability display while displaying a grayscale value of the target that serves as a basis for subsequent angle measurements; and A goniometric rotation device including a pair of servo motors for placing a rotation point on a normal to an axis-aligned surface of the display.

2. The system of claim 1, wherein the object tracking device is a spectroradiometer.

3. The system of claim 1, wherein the configuration file comprises a list of instructions, including: a list of angles classified based on optimized paths for reducing travel time to each location on the display; and A plurality of RGB input values ​​are given to the display.

4. The system of claim 3, wherein the plurality of RGB input values ​​include primary colors and a white point at a reference position, The reference position is a position where the surface normal of the display faces the object tracking device.

5. The system of claim 1, wherein the pair of servo motors of the angular rotation device comprises: A first servo motor for rotating the base; and A second servo motor is used to rotate the display to precisely place the rotation point on the axis alignment surface normal of the display.

6. The system according to claim 1, further comprising A gimbal with PLC precision is used to orient the display in 2-DOF, enabling a hemispherical data set.

7. The system according to claim 1, further comprising The image processor of the display is used to process the RGB value of the target.

8. The system of claim 1, further comprising: a rotation converter for converting angle values ​​into a common orientation; and Buffer for storing converted angle values.

9. The system according to claim 1, further comprising Multiple reference measurements, including: RGB primary color measurement results at the reference position; and Target white at reference position, followed by light control measurements.

10. The system of claim 9, wherein the light control measurements include: an optimized position list for sending position values ​​to the yaw axis and the roll axis of the pair of servo motors; a control message received when the pair of servo motors reaches a relative position with respect to a target; as well as A command issued to the object tracking device to initiate measurement of the relative position of the target.

11. The system of claim 1, wherein the object tracking device is a Laser Imaging, Detection, and Ranging (LiDAR) device.

12. A method for applying correction to an image rendered on a display, the method comprising: receiving calibration data including a brightness correction lookup table; Receive the target color space primaries and white point from the pole positions, wherein the pole position is located at the pole of a hemisphere formed above the display; calculating a normalized primary color matrix including tristimulus values ​​using the target color space primaries and the white point; Calculate chromaticity correction using normalized primary color matrix; The brightness correction is calculated using the RGB values ​​of the display and a brightness correction lookup table.

13. The method according to claim 12, further comprising Remove outliers from the calibration data within a given threshold.

14. The method according to claim 12, further comprising Transform the tristimulus values ​​of the normalized primary color matrix from radial coordinates to polar coordinates.

15. The method according to claim 12, further comprising A chromaticity correction is applied to the RGB values ​​of the display.

16. The method of claim 12, wherein calculating the brightness correction comprises: Fitting polynomials using linear least squares; and Solve for the 1-D normalized brightness correction factor.

17. The method according to claim 12, further comprising Brightness correction is applied by limiting the correction ratio of the RGB values ​​of the display to half or double.

18. The method according to claim 17, further comprising The brightness correction is pre-computed by fitting the correction ratio and the brightness factor on a Cartesian plane.

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