Characterizing the performance of an optical system with a color camera

Abstract

A device, system, and method are provided for processing the output of a color camera so that the color camera can be used to measure the color uniformity and resolution of an optical system. The processing includes converting the output of the color camera into an XYZ color space using a transformation matrix. The transformation matrix is ​​generated by capturing color images and colorimeter measurements of three different wavelength ranges of light. The processing also includes overcoming the debayering effect of the color camera and measuring the resolution of the optical system using an optical test target displayed by the optical system. The optical test target has a uniform appearance along the direction of uniformity. The resolution is determined based on a one-dimensional image generated by performing mathematical operations along the direction of uniformity.

Description

[Technical Field]

[0001] Related Applications This application claims the benefit of Application No. 63 / 439,287, filed January 17, 2023, which is incorporated herein by reference in its entirety.

[0002] The present disclosure relates generally to color imaging, and more particularly to characterizing the performance of optical systems using color cameras. [Background technology]

[0003] Analyzing an optical system typically involves characterizing its color uniformity and resolution. However, to characterize the resolution of an optical system, the measurement system typically requires a higher resolution than the optical system being measured. In addition, to accurately measure the color uniformity of an optical system, the measurement system typically must output measurements of color uniformity in XYZ values ​​from the CIE 1931 color space. XYZ values ​​from the CIE 1931 color space are commonly used as a standard for quantifying and communicating color. To output values ​​in XYZ, most measurement systems use imaging colorimeters.

[0004] Near-eye displays are often used in applications such as virtual reality (VR) headsets or augmented reality (AR) headsets. The eye motion box (EMB) refers to a defined space or volume within which a user's eyes can move while still being able to clearly see the image generated by the near-eye display (NED) system. The eye motion box determines the range of natural eye movement permitted without losing the clarity or focus of the displayed image. If the EMB is too small, users may frequently find parts of the image blurred or out of view, which can be uncomfortable and disrupt the immersive experience. Therefore, measuring and optimizing the EMB is important to ensure a comfortable and effective viewing experience for users. Summary of the Invention

[0005] As opposed to using a standard imaging colorimeter, it is preferable to use a simple off-the-shelf "normal" color camera to measure the color uniformity and resolution of an optical system.

[0006] A problem with measuring the properties of an EMB (eye motion box) using a standard imaging colorimeter is the size of the colorimeter, which is usually too large to easily scan different positions of the EMB in the WG (waveguide) of a NED (near eye display) system.

[0007] A problem with measuring optical properties using a standard color camera is that color cameras use a demosaicing algorithm (also known as the debayering effect) to generate color images. Debayering is applied to images captured by the camera using a Bayer filter (i.e., a grid of red, green, and blue filters) on the image sensor. Because each sensor pixel captures light from only one primary color, the raw image data contains incomplete color information. The demosaicing algorithm then interpolates the missing color for each pixel by analyzing neighboring pixels, effectively reconstructing a full-color image. The debayering process of camera image interpolation reduces the camera's resolution.

[0008] The present disclosure provides devices, systems, and methods for processing the output of an off-the-shelf color camera so that the color camera can be used to measure the color uniformity and resolution of an optical system.

[0009] In one embodiment, the present disclosure provides devices, systems, and methods for converting the output of a camera to an XYZ color space using a transformation matrix generated by comparing the output of the camera to the output of a colorimeter for light in at least three different wavelength ranges.

[0010] In another embodiment, the present disclosure provides devices, systems, and methods for overcoming debayering in color cameras, such that a color camera can be used to measure the resolution of an optical system by using a raw green channel image of an optical test target from the color camera and performing mathematical operations along the direction of homogeneity of the optical test target.

[0011] Although certain features will be described with respect to embodiments of the present invention, features described with respect to a given embodiment may be employed in connection with other embodiments. The following description and accompanying drawings refer to specific exemplary embodiments of the present invention. However, these embodiments are indicative of but a few of the various ways in which the principles of the present invention may be employed. Other objects, advantages, and novel features according to aspects of the present invention will become apparent from the following detailed description when considered in conjunction with the drawings. [Brief explanation of the drawings]

[0012] The accompanying drawings, which are not necessarily to scale, illustrate various aspects of the present invention, in which like reference numerals are used to refer to the same or similar parts in the various drawings.

[0013] [Figure 1] FIG. 1 is an exemplary block diagram of a measurement system for measuring optical properties of an optical system. [Figure 2] FIG. 1 is an exemplary block diagram of a processor circuit that receives the output of a color camera and a colorimeter based on light emitted by a light source. [Figure 3] 1 is an exemplary block diagram of red, green, and blue pixels in a color camera. [Figure 4] 1 shows a typical optical test target. [Figure 5] 5 illustrates an exemplary raw green test image of the optical test target of FIG. 4. [Figure 6] 6 shows an exemplary test one-dimensional image of the exemplary raw green test image of FIG. 5. [Figure 7]1 shows an exemplary raw green test image of a cross-shaped test target.

[0014] The present invention will be described in detail below with reference to the drawings, in which each element having a reference number is similar to other elements having the same reference number, regardless of any letter designation that follows the reference number. In this text, a reference number with a particular letter designation after it refers to the particular element with that number and letter designation, and a reference number without a particular letter designation refers to all elements with the same reference number, regardless of any letter designation that follows the reference number in the drawings. DETAILED DESCRIPTION OF THE INVENTION

[0015] The present disclosure provides devices, systems, and methods for processing the output of an off-the-shelf color camera so that the color camera can be used to measure the color uniformity and resolution of an optical system. This process involves converting the camera's output from one color space (e.g., RGB) to the XYZ color space using a transformation matrix. This transformation matrix is ​​generated by capturing color images of three different wavelength ranges of light. A colorimeter is also used to measure the light in the three different wavelength ranges in the XYZ color space. The outputs of the colorimeter and the color camera for the three wavelength ranges of light are compared to generate a transformation matrix for converting from the camera's color space to the XYZ color space. The output of the color camera is then multiplied by the transformation matrix to convert it to the XYZ color space. This process also involves overcoming the debayering effect of the color camera to measure the resolution of the optical system. To measure the resolution of the optical system, the color camera captures an image of an optical test target displayed by the optical system. The optical test target has a known pattern of contrasting structures with known spacing so that the optical test target has a uniform appearance along the direction of uniformity. The one-dimensional image is generated by performing mathematical operations (e.g., summing, averaging, convolution, etc.) along the direction of homogeneity of the optical test target. The resolution of the optical system is then determined based on the known spacing of the contrasting structures of the optical test target and the test one-dimensional image.

[0016] 1, there is shown a measurement system 10 for measuring optical properties of an optical system 12 using an optical test target 14 (FIG. 4) and a light source 16. The measurement system 10 includes a color camera 20, a colorimeter 24, and a computing device 30.

[0017] As will be explained in further detail below, computing device 30 converts the output of color camera 20 to XYZ color space using light source 16 and based on the output of colorimeter 24. Computing device 30 also measures the resolution of optical system 12 from an image produced by color camera 20 imaging optical system 12 displaying optical test target 14. Computing device 30 includes processor circuitry 32 for performing these tasks.

[0018] Referring to FIG. 2, when converting the output of color camera 20 to XYZ color space, processor circuit 32 determines colorimeter output 34 and camera output 36 for three wavelength ranges of light. Because XYZ color space (also called tristimulus photometry) is additive, light of three different wavelength ranges can be used. For example, if both red and blue light are displayed, the XYZ values ​​are equal to the linear addition of the two separate light sources (i.e., red and blue light). Because of this additivity, each color can be represented by a linear vector with three elements. For example, red light can be represented as [1;0;0], green light can be represented as [0;1;0], blue light can be represented as [0;0;1], and white light can be represented as the sum [1;1;1]. By using light of three different wavelength ranges (e.g., red, green, and blue), XYZ values ​​can be measured by colorimeter 24 and compared to the output of color camera 20.

[0019] The three different wavelength ranges may be referred to as three different colors. Each of the three different colors may be a Gaussian distribution of wavelengths distributed around a dominant wavelength (also referred to as a center wavelength). These three different colors may correspond to the three colors (i.e., dimensions) of the color space of the color camera. The optical system may also include a light-emitting source that outputs three colors (i.e., wavelength ranges of light). The three different colors may correspond to the colors of the light-emitting source of the optical system.

[0020] In one embodiment, the light source may be the light emitting source of the optical system, i.e., the color camera and colorimeter may measure the output of the light emitting source of the optical system.

[0021] In another embodiment, the light source may be a separate device from the light-emitting source of the optical system, but the light source may have similar output characteristics (e.g., wavelength range, intensity, etc.) as the light-emitting source of the optical system. This separate light source may have the same emission characteristics as the light-emitting source of the optical system.

[0022] For each of the three wavelength ranges, processor circuit 32 receives a colorimeter output 34 from colorimeter 24 based on a measurement of light source 16 while light source 16 emits light 38 having a wavelength. That is, light source 16 emits light 38 having a wavelength, colorimeter 24 measures the emitted light 38 having a wavelength, and processor circuit 32 receives a colorimeter output 34 of this measurement. Similarly, for each of the three wavelength ranges, processor circuit 32 also receives a camera output 36 from camera 20 based on an imaging of emitted light 38 having a wavelength. That is, light source 16 emits light 38 having a wavelength, camera 20 images emitted light 38 having a wavelength, and processor circuit 32 receives a camera output 36 of this imaging.

[0023] As described above, the colorimeter output and the camera output are in different color spaces. That is, while the colorimeter output is in the XYZ color space, the camera output is in a camera color space that is different from the XYZ color space. The colorimeter 24 can be any suitable device for outputting measurements of incident light in the XYZ color space. For example, the colorimeter can be a point colorimeter that outputs a single XYZ value for the incident light. In this way, instead of using an imaging colorimeter as described above (which outputs an array of measurements of a scene), the present disclosure can utilize a point colorimeter.

[0024] In one embodiment, the camera color space may be in the RGB (red, green, blue) color space. For example, the output of the camera may include an array of pixels. For each pixel in the array of pixels, the camera output may include a red value, a green value, and a blue value, such that each pixel in the array of pixels represents a vector formed by its red value, its green value, and its blue value.

[0025] Color camera 20 may be any suitable device for outputting an image including an array of pixels in an additive color space (e.g., RGB). That is, color camera 20 may include a variety of configurations and components. For example, color camera 20 may include an image sensor (e.g., a CCD or CMOS sensor), a digital signal processor (DSP), a lens assembly, and integrated circuits for image processing. Color camera 20 may also include ancillary hardware such as an autofocus mechanism, an optical image stabilization module, memory (e.g., built-in memory, removable storage media, etc.), etc.

[0026] In addition to the camera color space being in the RGB color space, the three wavelength ranges of light emitted by light source 16 can include red, green, and blue. For example, the three wavelength ranges of light can be emitted separately (i.e., at different times) so that the measurement and imaging of a first wavelength (e.g., red light), a second wavelength (e.g., green light), and a third wavelength (e.g., blue light) by the colorimeter and camera occur at different, non-overlapping times. In this manner, red light, green light, and blue light can be imaged by color camera 20 and measured separately by colorimeter 24, so that the camera output 36 and the colorimeter output 34 are perceived separately for each dimension (e.g., R, G, and B) of the camera color space.

[0027] Light source 16 can be any suitable structure for emitting light. For example, light source 16 can include one or more light-emitting diodes (LEDs), organic LEDs (OLEDs), micro LEDs, laser diodes, mini LEDs, quantum dot (QD) conversion, phosphor conversion, excimer lamps, multi-photon combinations, or SLM wavefront manipulation. Light source 16 can include additional components (e.g., a color wheel) for modifying the wavelength of the emitted light. For example, light source 16 can be a display, a waveguide, or the like.

[0028] Continuing the example above in RGB color space, the camera output 36 for red wavelengths of light is [R r ;G r ;B r ] T and the camera output for the green wavelength of light can be expressed as [R g ;G g ;B g ] T and the camera output for the blue wavelengths of light can be expressed as [R b ;G b ;B b ] T Similarly, the colorimeter output for red wavelengths of light can be expressed as [X r ;Y r ;Z r ] T and the colorimeter output for green wavelengths of light can be expressed as [Xg ;Y g ;Z g ] T The colorimeter output for blue wavelengths of light is expressed as [X b ;Y b ;Z b ] T It can be expressed as:

[0029] The processor circuit 32 generates a colorimeter matrix (M xyz ) such that the colorimeter outputs 34 for each of the three wavelength ranges form a column of the matrix. Similarly, the processor circuit 32 generates a camera matrix (M カメラ ) are generated such that the camera outputs 36 for each of the three wavelength ranges form columns of the matrix.

[0030] Continuing with the above example for RGB emission and RGB color space, the camera matrix and colorimeter matrix can be defined as follows:

[0031]

number

[0032] The processor circuit 32 is xyz and M カメラ To do so, the processor circuitry converts the camera output to the XYZ color space using M xyz to M カメラ By multiplying it by the inverse matrix of the transformation matrix (M 変換 ) M 変換 =M xyz *M カメラ -1

[0033] The processor circuit 32 receives the output of the camera 36 and applies M 変換 By applying 変換Use M for camera output 36. 変換 By applying the formula: the transformed output 40 is in the XYZ color space. The processor circuit 32 also outputs the transformed output 40.

[0034] In one embodiment, the output of the camera is an image comprising an array of pixels. 変換 is a pixel in the pixel array. 変換 The transformation can be applied to the output of camera 36 by multiplying by M. Alternatively, instead of transforming each pixel of the camera output, processor circuit 32 can group each of the pixels into pixel blocks. Each pixel block may be a group of adjacent pixels (e.g., 10x10 pixels, 100x100 pixels, etc.). For each pixel block, processor circuit 32 can calculate red, green, and blue values ​​based on the average of the red, green, and blue values ​​of the pixels within the pixel block. Processor circuit 32 then applies M to the vector of red, green, and blue values ​​for each pixel block. 変換 By multiplying the camera output by M 変換 can be applied.

[0035] 3, 4, and 5, when measuring the resolution of optical system 12, processor circuit 32 receives raw image 50 from color camera 20. Raw image 50 is an image of optical system 12 displaying optical test target 14. The raw image includes green image data 52. This green image data 52 is analyzed to determine the resolution of optical system 12. That is, it is green image data 52 instead of a monochrome image.

[0036] The color camera 20 may be a Bayer-based color camera 20. As shown in Figure 3, the raw image 50 may include an array of pixels 54 having different color sensitivities. The pixel array 54 may have a checkerboard structure with primarily green pixels (G1, G3, G5, G7, G9, G11, G13, G15, G17, G19, G21, G23, G25) intermixed with a combination of red pixels (R2, R4, R12, R14, R22, R24) and blue pixels (B6, B8, B10, B16, B18, B20).

[0037] As an example, the monochromatic image from color camera 20 is not used in the monochromatic gray-level mode because the gray-level value of each pixel is a linear combination of each pixel's RGB values ​​according to the photopic weighting. This linear combination of RGB values ​​results in smoothing of the image in the monochromatic mode because each pixel's value overlaps with its nearest neighbors and its next nearest neighbors. This linear combination can reduce the resolution of the monochromatic image. For this reason, processor circuit 32 uses green image data 52 instead of the monochromatic image output by color camera 20. Because the photopic curve of the human eye is similar to the photopic curve of a green pixel, green image data 52 may be used (i.e., instead of red and blue image data).

[0038] As explained above, raw image 50 is an image of optical system 12 displaying optical test target 14. Optical test target 14 is displayed by itself because optical test target 14 has a known pattern of symmetrical structures 60 with known spacing 62, such that optical test target 14 has a uniform appearance along direction of homogeneity 64. These known characteristics of optical test target 14, and direction of homogeneity 64, are used to calculate the resolution of optical system 12.

[0039] In one embodiment, the optical test target 14 may be a Ronchi ruling, as shown in Figure 4. In this example, the direction of homogeneity 64 is vertical, although the direction of homogeneity 64 may also be horizontal, vertical, or any suitable direction.

[0040] The processor circuit 32 separates the green image data into a raw green test image 56 having pixels 54. For example, the green image data can be separated by changing the gain of the color camera so that the output of the red and blue pixels is zero. Figure 5 shows a raw green test image 56 of the optical test target 14 shown in Figure 4. The raw green test image 56 has a checkerboard appearance, with black pixels representing red and blue pixels, as shown in Figure 3.

[0041] The processor circuitry 32 generates a test one-dimensional image 66 based on a mathematical operation performed on the raw green test image 56 along the direction of homogeneity 64. The mathematical operation may include at least one of convolution, summation, or averaging. As an example, a one-dimensional image 66 generated from summing the raw green test image 56 along the vertical direction (i.e., the direction of homogeneity 64) is shown in FIG.

[0042] In one embodiment, the mathematical operation may include convolution along the direction of homogeneity with an array having an orientation that matches the direction of homogeneity. For example, if the direction of homogeneity is horizontal, the array may be a horizontal array with a horizontal orientation. Similarly, if the direction of homogeneity is vertical, the array may be a vertical array with a vertical orientation.

[0043] The processor circuit 32 determines and outputs 68 the resolution of the optical system 12 along the direction of homogeneity 64 based on the known spacing 62 of the contrasting structures 60 of the optical test target 14 and the test one-dimensional image 66. For example, the optical system 12 may be determined to have a resolution that at least matches the known spacing 62 of the optical test target 14 when the contrasting structures 60 are discernible in the test one-dimensional image 66. Similarly, the optical system 12 may be determined to have a resolution that falls below the known spacing 62 when the contrasting structures 60 are not discernible in the test one-dimensional image.

[0044] For example, when viewing optical test targets 14 having a known spacing 62 of 1 mm along the horizontal direction, if adjacent contrasting structures 60 are discernible in the test one-dimensional image 66, then optical system 12 may be determined to have a resolution of at least 1 mm. Conversely, if adjacent contrasting structures 60 are not discernible in the test one-dimensional image 66, then the resolution of optical system 12 along the horizontal dimension may be determined to be less than 1 mm.

[0045] In another example, a single optical test target 14 may be used. The measured contrast of contrasting structures 60 in a test one-dimensional image of the optical test target 14 may be used to determine the resolution of the system. For example, 20% contrast may be recognized as correlating to a particular resolution for the optical test target 14. Alternatively, the contrast of the optical test target 14 may be used as a measure of the resolution of the optical system.

[0046] Contrasting structures 60 may be determined to be recognizable when the contrast between the contrasting structures 60 is greater than a minimum detection threshold. For example, the contrast between contrasting structures 60 in the test one-dimensional image 66 may be determined based on the maximum and minimum values ​​of the test one-dimensional image 66. As an example, the average maximum value of the test one-dimensional image 66 (e.g., the average value of the peaks of the sinusoidal structures shown in FIG. 6) may be determined, and the average minimum value of the test one-dimensional image 66 (e.g., the average value of the valleys of the sinusoidal structures shown in FIG. 6) may be determined. The contrast may be determined based on the difference between the maximum and minimum values.

[0047] The processor circuitry 32 can determine the vertical and horizontal resolution of the optical system 12 by performing the process described above twice: once when the optical system displays an optical test pattern having a uniform horizontal direction 64 (i.e., to determine the horizontal resolution), and twice when the optical system displays an optical test pattern having a uniform vertical direction 64 (i.e., to determine the vertical resolution).

[0048] Alternatively, instead of measuring vertical and horizontal resolution separately, a cross-shaped optical test target can be used, as shown in FIG. 7. FIG. 7 shows a raw green test image of a cross-shaped optical test target. Below and to the left of the raw green test image are test 1D images representing vertical and horizontal summation, respectively. As shown, the camera captures only half the pixels (i.e., only green pixels), but the camera resolution is not compromised and the summed 1D curve is unaffected. By measuring the width of the cross, the system's line spread function and system modulation transfer function (MTF) can be analyzed (i.e., by performing a Fourier transform of the optical system's line spread function).

[0049] The processor circuitry 32 may output the determined resolution and converted output in any suitable manner, for example, by storing the data in a memory, transmitting the data over a network interface, displaying the data on a display, etc.

[0050] Computing device 30 may encompass a variety of configurations and designs. For example, computer 10 may be implemented as a single device such as a server, desktop computer, laptop, or other standalone unit. These individual devices may incorporate essential components such as a central processing unit (CPU), memory modules (including random access memory (RAM) and read-only memory (ROM)), storage devices (such as solid-state drives or hard disk drives), and various input / output (I / O) interfaces. Alternatively, computing device 30 may comprise a network of interconnected computing devices to form a more complex, integrated system. This may include a server cluster, a distributed computing environment, or a cloud-based infrastructure, where multiple devices are linked via a network interface to operate cohesively, often providing enhanced processing power, data storage, and redundancy.

[0051] The processor circuitry 32 may have various implementation forms. For example, the processor circuitry 32 may include any suitable device, such as a processor (e.g., a CPU), a programmable circuit, an integrated circuit, a memory and I / O circuit, an application-specific integrated circuit, a microcontroller, a complex programmable logic device, or another programmable circuit. The processor circuitry 32 may also include a non-transitory computer-readable medium, such as a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM, or flash memory), or any other suitable medium. Instructions for performing the methods described below may be stored in a non-transitory computer-readable medium and executed by the processor circuitry 32. The processor circuitry 32 may be communicatively coupled to the computer-readable medium and a network interface through a system bus, a motherboard, or any other suitable structure known in the art.

[0052] All range and ratio limits disclosed in the specification and claims may be combined in any manner. Unless otherwise specified, references to "a," "an," and / or "the" may include one or more, and references to items in the singular may also include items in the plural.

[0053] While the present invention has been shown and described with respect to a particular embodiment or embodiments, equivalent alterations and modifications will occur to those skilled in the art upon reading and understanding this specification and the accompanying drawings. In particular, with respect to the various functions performed by the elements (components, assemblies, devices, compositions, etc.) described above, the terms used to describe such elements (including references to "means") are intended, unless otherwise indicated, to correspond to any element that performs the designated function of the described element (i.e., is functionally equivalent), even if it is not structurally equivalent to the disclosed structure that performs that function in the exemplary embodiment or embodiments illustrated herein. In addition, while a particular feature of the invention may be described above with respect to only one or more of the illustrated embodiments, such feature can be combined with one or more other features of other embodiments, as may be desired and advantageous for any given or particular application.

Claims

1. 1. A computing device for measuring optical properties of an optical system from an image produced by a color camera based on the output of a colorimeter, an optical test target, and using a light source, the computing device comprising: a processor circuit; converting the output of the color camera into an XYZ color space based on the output of the colorimeter; The colorimeter output and the camera output for three wavelength ranges of light are calculated for each of the three wavelength ranges. receiving the colorimeter output from the colorimeter based on measurements of the light source while the light source is emitting light having the wavelength, the colorimeter output being in the XYZ color space; receiving the camera output from the camera based on imaging the light source while the light source is emitting light having the wavelength, the camera output being in a camera color space different from the XYZ color space; The colorimeter outputs for the three wavelength ranges are combined to form a colorimeter matrix (M ｘｙｚ ) such that the colorimeter outputs for each of the three wavelength ranges form a column of the matrix; The camera outputs for the three wavelength ranges are combined to form a camera matrix (M カメラ ), such that the camera outputs for each of the three wavelength ranges form a column of the matrix; Said M ｘｙｚ To M カメラ By multiplying the inverse matrix of 変換 ) and receiving the output of the camera; M 変換 generating a transformed output by applying a transform to the output of the camera, such that the transformed output is in the XYZ color space; outputting the transformed output; and a resolution of the optical system for displaying the optical test target; receiving a raw image from the color camera of the optical system that displays the optical test target; the raw image includes green image data; receiving the optical test target having a known pattern of contrasting structures with known spacing such that the optical test target has a uniform appearance along a direction of homogeneity; separating the green image data into a raw green test image comprising pixels; generating a test one-dimensional image based on mathematical operations performed on the raw green test image along the direction of homogeneity; determining the resolution of the optical system along the direction of homogeneity based on the known spacing of the contrasting structures of the optical test target and the test one-dimensional image; and outputting the determined resolution.

2. The computing device of claim 1 , wherein the light source is part of the optical system being measured.

3. 1. A computing device for converting an output of a color camera to an XYZ color space based on an output of a colorimeter and using a light source, the computing device including a processor circuit, the processor circuit comprising: The colorimeter output and the camera output for three wavelength ranges of light are calculated for each of the three wavelength ranges. receiving the colorimeter output from the colorimeter based on measurements of the light source while the light source is emitting light having the wavelength, the colorimeter output being in the XYZ color space; receiving the camera output from the camera based on imaging the light source while the light source is emitting light having the wavelength, the camera output being in a camera color space different from the XYZ color space; The colorimeter outputs for the three wavelength ranges are combined to form a colorimeter matrix (M ｘｙｚ ) such that the colorimeter outputs for each of the three wavelength ranges form a column of the matrix; The camera outputs for the three wavelength ranges are combined to form a camera matrix (M カメラ ), such that the camera outputs for each of the three wavelength ranges form a column of the matrix; Said M ｘｙｚ To M カメラ By multiplying the inverse matrix of 変換 ) and receiving the output of the camera; The output of the camera is 変換 generating a transformed output by applying and outputting the transformed output.

4. The computer device of claim 3 , wherein the camera color space is in the red, green, and blue (RGB) color space.

5. the output of the camera comprises an array of pixels; 4. The computer device of claim 3, wherein each pixel in the array of pixels includes a red value, a green value, and a blue value, whereby each pixel in the array of pixels represents a vector formed by the red value, the green value, and the blue value.

6. M 変換 M 変換 6. The computing device of claim 5, wherein the output of the camera is applied by multiplying the output of the camera by

7. the processor circuitry comprises: grouping each of said pixels into a pixel block comprising a group of adjacent pixels; and for each of the pixel blocks, calculating red, green, and blue values ​​based on averages of red, green, and blue values ​​of the pixels in the pixel block; M 変換 is added to the vector of red, green, and blue values ​​of each pixel block by M 変換 6. The computing device of claim 5, wherein the output of the camera is applied by multiplying the output of the camera by

8. The computing device of claim 3 , wherein the three wavelength ranges of light include red, green, and blue.

9. The camera output for red wavelengths of light is [R ｒ ;G ｒ ;B ｒ ] Ｔ and The camera output for green wavelengths of light is [R ｇ ;G ｇ ;B ｇ ] Ｔ and The camera output for blue wavelengths of light is [R ｂ ;G ｂ ;B ｂ ] Ｔ and [Equation 1] and The colorimeter output for the red wavelengths of the light is [X ｒ ; Y ｒ ;Z ｒ ] Ｔ and The colorimeter output for the green wavelength of the light is [X ｇ ; Y ｇ ;Z ｇ ] Ｔ and The colorimeter output for the blue wavelengths of the light is [X ｂ ; Y ｂ ;Z ｂ ] Ｔ and [Equation 2] 9. The computer device of claim 8, wherein:

10. The computing device of claim 3 , wherein the colorimeter is a point colorimeter.

11. 4. The computing device of claim 3, wherein the three wavelength ranges of light are emitted separately such that the imaging of a first wavelength with the colorimeter and the camera, the imaging of a second wavelength with the colorimeter and the camera, and the imaging of a third wavelength with the colorimeter and the camera occur at different, non-overlapping times.

12. 1. A computing device for measuring resolution of an optical system from an image produced by a color camera capturing an image of the optical system displaying an optical test target, the computing device comprising: a processor circuit; receiving a raw image from the color camera of the optical system that displays the optical test target; the raw image includes green image data; receiving the optical test target having a known pattern of contrasting structures with known spacing such that the optical test target has a uniform appearance along a direction of homogeneity; separating the green image data into a raw green test image comprising pixels; generating a test one-dimensional image based on mathematical operations performed on the raw green test image along the direction of homogeneity; determining the resolution of the optical system along the direction of homogeneity based on the known spacing of the contrasting structures of the optical test target and the test one-dimensional image; and outputting the determined resolution.

13. The computing device of claim 12 , wherein the direction of uniformity comprises horizontal or vertical.

14. The computing device of claim 12 , wherein the mathematical operation comprises at least one of a convolution, an addition, or an averaging.

15. the direction of the homogeneity comprises horizontal or vertical; The mathematical operation comprises a convolution along the direction of homogeneity with a sequence having an orientation that matches the direction of homogeneity, resulting in: if the direction of the homogeneity is horizontal, the array is a horizontal array having a horizontal orientation; The computing device of claim 14 , wherein if the direction of homogeneity is vertical, the array is a vertical array having a vertical orientation.

16. The optical system is determined to have a resolution, the resolution being: the contrasting structures correspond at least to the known spacing when they are recognizable in the test one-dimensional image; The computing device of claim 12 , wherein the known spacing is less than when the contrasting structures are not discernible in the test one-dimensional image.

17. The computing device of claim 12 , wherein the optical test target is a Ronchi ruling.

18. 1. A measurement system for measuring optical properties of an optical system using an optical test target and a light source, the measurement system comprising: a color camera configured to capture and output images in a color space; a colorimeter configured to output values ​​in the XYZ color space; A measurement system comprising a computing device according to any one of claims 1 to 17.

Images