A color speckle measurement method and apparatus thereof

Abstract

The present application relates to the field of optical metrology and imaging technology, and particularly to a color speckle measurement method in a laser display system and a measurement device using the method. The measurement method comprises: step a) imaging a target surface showing a color speckle pattern on a modulation plane of a spatial light modulator through an imaging module; step b) dividing the modulation plane into multiple spatial regions, sequentially selecting the spatial regions, guiding the light signals of the selected spatial regions into a dispersion element for spectral dispersion, and then collecting the dispersed spectral data by a first image sensor until the spectral data of all spatial regions on the modulation plane are collected; step c) reconstructing the collected spectral data into a three-dimensional hyperspectral data cube containing spatial and spectral dimensions according to the spatial position information corresponding to the spectral data; and step d) calculating and outputting speckle measurement indexes according to the three-dimensional hyperspectral data cube.

Description

Technical Field

[0001] This invention relates to the field of optical metrology and imaging technology, and in particular to a method and apparatus for quantitatively measuring and characterizing color speckle phenomena in laser display systems using spatial light modulation (SLM) technology. Background Technology

[0002] In recent years, laser display technology, with its superior performance—such as a wide color gamut, extremely high brightness, long lifespan, and high energy efficiency—has become an important development direction for next-generation display technology. From giant-screen cinemas to home projectors, the application of laser light sources has brought a qualitative leap to the visual experience. However, the inherent high coherence of lasers inevitably produces laser speckle when they illuminate optically rough surfaces (such as projection screens and walls). This granular pattern, formed by the random interference of countless secondary scattered waves, significantly reduces image sharpness and affects the visual experience.

[0003] In color laser display systems employing red (R), green (G), and blue (B) lasers, speckle problems are particularly complex and severe, manifesting as color speckle. Because the wavelengths of R, G, and B lasers are different and coherent, the speckle patterns they form in space are uncorrelated. This results in viewers seeing a mottled pattern composed of random colors (such as magenta, cyan, and yellow) when observing a uniform color patch (e.g., white). This not only reduces sharpness but also fundamentally distorts the accurate transmission of color information, causing far greater visual interference than monochrome speckle.

[0004] To objectively assess the severity of speckle, the industry typically uses speckle contrast ratio as a quantitative indicator. However, for colored speckle, traditional monochrome speckle contrast ratio is insufficient for a comprehensive evaluation. Therefore, international standards such as IEC 62906-5-4 Laser Display Devices Part 5-4: Optical Test Methods for Colored Speckle have defined more complex metrics, including luminance speckle contrast ratio, color speckle variance, color speckle covariance, and color speckle indices based on the CIE 1976 chromaticity diagram, to quantify the impact of colored speckle on human visual perception from multiple dimensions, such as luminance and chromaticity.

[0005] Currently, traditional methods for measuring colored speckle have certain limitations:

[0006] (1) Insufficient spectral resolution: Existing standard or traditional measurement methods usually rely on optical measurement devices with XYZ or RGB filters. These filters are essentially broadband filters that integrate optical signals over a wide wavelength range. This makes them unable to distinguish the speckle characteristics generated by different wavelengths of laser in a multi-primary-color laser system (e.g., using two red lasers, 638nm and 642nm, to broaden the color gamut), but instead alias them into an averaged result. Therefore, it is difficult to perform detailed diagnosis and optimization.

[0007] (2) Channel crosstalk and spectral mismatch of color camera: Color RGB camera obtains spectral data by sensing color through Bayer filter array, but its broad and overlapping spectral response curves will cause serious channel crosstalk; even if a monochrome camera + XYZ (or RGB) filter is used, "spectral mismatch" will occur due to the narrow band characteristics of laser, resulting in systematic deviation of speckle contrast in each channel.

[0008] (3) Unstable factors introduced by mechanical structure: Some traditional imaging colorimeters use rotating filter wheels to achieve multi-channel measurement. Long-term or high-speed operation of the filter wheels can easily introduce vibration, positioning error and cross-channel image registration error, which affects the measurement accuracy and stability.

[0009] Meanwhile, another method for acquiring spectral data is using a hyperspectral camera, which often employs mechanical push-brooms, rotating filter wheels, and other structures to achieve spatial or wavelength-direction scanning. These mechanical scanning structures have many moving parts, resulting in slow speed, limited accuracy, and susceptibility to vibration and registration errors, making them unsuitable for rapid and stable measurement of color speckle. Summary of the Invention

[0010] To address at least one of the problems in existing color speckle measurement methods, such as insufficient spectral resolution, filter spectral response mismatch, and slow mechanical scanning devices prone to vibration and registration errors, this invention proposes a color speckle measurement method and device based on spatial light modulation. By utilizing spatial light modulation technology, combined with hyperspectral imaging and a standard colorimetric calculation model, high-precision and high-stability quantitative measurement of color speckle can be achieved without the need for mechanical scanning.

[0011] The present invention provides a method for measuring color speckle, comprising the following steps:

[0012] Step a): An image of a target surface exhibiting a colored speckle pattern is projected onto the modulation plane of a spatial light modulator using an imaging module;

[0013] Step b): Divide the modulation plane into multiple spatial regions, select the spatial regions in sequence, and guide the light signal of the selected spatial region into a dispersive element for spectral dispersion. Then, a first image sensor collects the spectral data after dispersion until the spectral data of all spatial regions on the modulation plane are collected.

[0014] Step c): The collected spectral data is reconstructed into a three-dimensional hyperspectral data cube containing spatial and spectral dimensions based on its corresponding spatial location information. ;

[0015] Step d): Based on the three-dimensional hyperspectral data cube By combining a preset chromaticity matching function or a filter spectral response curve, at least one of the following speckle measurement indicators is calculated and output: luminance speckle contrast, luminance speckle distribution, variance of color speckle based on the CIE1976 chromaticity diagram, covariance of color speckle, and color speckle distribution map.

[0016] Step a) further includes: the image captured by the imaging lens of the imaging module is divided into a main optical path and an auxiliary optical path by a beam splitting system, the main optical path is imaged on the modulation plane, the auxiliary optical path is imaged on the second image sensor, the sharpness score of the image formed by the second image sensor is calculated, and the imaging lens is adjusted using the sharpness score to make the image on the modulation plane clear.

[0017] Furthermore, in step b), the spatial light modulator selects the spatial regions sequentially by selecting row by row or column by column until all the spatial regions within the modulation plane are selected.

[0018] Further, step c) includes at least one calibration step among radiance calibration, spectral calibration, and geometric calibration of the three-dimensional hyperspectral data cube.

[0019] Further, step d) includes calculating the XYZ tristimulus values, and then calculating the speckle measurement index based on the XYZ tristimulus values. The tristimulus values ​​are obtained through a two-dimensional image. , , The calculation formula is as follows:

[0020]

[0021]

[0022]

[0023] in, This represents the color matching function of the CIE 1931 standard; (x, y) represents the spatial pixel.

[0024] Furthermore, the method for calculating the speckle measurement index includes at least one of the following:

[0025] The brightness speckle contrast:

[0026] Represents the brightness speckle contrast. Represents spatial standard deviation, Represents the spatial average;

[0027] The speckle distribution of the photometric speckle; statistics The distribution of pixel values ​​in the image is used to generate the brightness histogram, which is used to represent the speckle distribution of photometric speckle.

[0028] The variance and covariance of the colored speckle: , , The image is converted pixel by pixel to CIE 1976 u'v' chromaticity coordinates, resulting in... and The conversion formula for two chroma images is:

[0029]

[0030]

[0031] Then according to and Image, calculate the variance of colored speckle. , Covariance :

[0032]

[0033]

[0034]

[0035] in This represents calculating the spatial average value over all pixels in an image;

[0036] Color speckle distribution diagram: Plotting pixels on the CIE 1976 chromaticity diagram The scatter distribution.

[0037] The present invention also provides a color speckle measuring device for implementing the above-described color speckle measuring method, the measuring device comprising:

[0038] An imaging lens is used to image a target surface that displays a colored speckle pattern;

[0039] A spatial light modulator is disposed in the main optical path. The modulation plane of the spatial light modulator is used to receive the main beam imaged by the imaging lens and to perform spatial light modulation on the image of the target surface so as to sequentially conduct the light signal of the image in different regions.

[0040] A beam control element is disposed in the imaging module and the space, for receiving the main beam from the imaging module and controlling the polarization, direction, displacement and rotation of the main beam;

[0041] A dispersive element is used to receive the optical signal transmitted from the spatial light modulator and disperse it according to wavelength;

[0042] A first image sensor is used to detect the spectral signal after dispersion by the dispersive element;

[0043] The main control system includes a control unit and a data processing unit. The control unit is used to control the spatial light modulator to divide its modulation plane into multiple spatial regions, and sequentially turn on each of the spatial regions, and synchronously control the first image sensor to perform exposure and data acquisition. The data processing unit is connected to the first image sensor and the control unit, and is configured to: reconstruct a three-dimensional hyperspectral data cube based on a series of spectral signals acquired by the first image sensor, and calculate and output at least one of the color speckle measurement indicators by combining a preset color matching function or filter spectral response curve.

[0044] Furthermore, the measuring device includes a beam splitting system and a focusing module: the beam splitting system is disposed after the imaging lens and is used to split the imaging beam formed by the imaging module into a main optical path and an auxiliary optical path; the focusing module includes a second image sensor disposed in the auxiliary optical path, used to acquire an image of the target surface to assist focusing, the photosensitive plane of the second image sensor and the modulation plane are located at the image side position of the equivalent optical path, the second image sensor is connected to the control unit and the data processing unit, the data processing unit is also used to process the image from the second image sensor and calculate the sharpness score of the image, and the control unit is also used to adjust the focal length of the imaging lens according to the sharpness score.

[0045] Alternatively, the first image sensor and the second image sensor may be any one of CMOS, CCD and InGaAs sensors.

[0046] Alternatively, the spatial light modulator is a digital micromirror array or a liquid crystal on silicon, wherein the micromirror array plane of the digital micromirror array forms the modulation plane, and the pixel array plane of the liquid crystal on silicon forms the modulation plane;

[0047] And / or, the beam control element is a total internal reflection prism, a mirror, a lens, or a polarization control element;

[0048] And / or, the dispersive element is a diffraction grating or a high-dispersion prism.

[0049] This invention utilizes a spatial light modulator as a programmable spatial selector, electronically selecting light signals from different regions of the target image to achieve completely non-mechanical spatial scanning. This avoids a series of problems introduced by mechanical movement in traditional pushbroom hyperspectral analyzers or optical measurement devices with filter wheels, such as vibration, positioning errors, wear, and speed limitations. Secondly, this invention processes the hyperspectral data obtained after scanning with the spatial light modulator to obtain more accurate XYZ tristimulus values, thereby obtaining more precise brightness speckle contrast and color speckle indices. Finally, this invention employs a digital micromirror switch in a selected spatial region to achieve non-mechanical scanning, which is faster, more stable, and provides higher data quality than mechanical scanning, making it particularly suitable for rapid production line inspections or R&D environments requiring long-term continuous operation.

[0050] This invention's "first acquire the spectrum, then calculate precisely" approach eliminates the uncertainties and errors introduced by physical filters. It enables the calculation of highly accurate color speckle evaluation indicators that fully conform to industry standard definitions, achieving a qualitative leap in measurement precision. Users can utilize this data to conduct in-depth analysis of speckle characteristics at any narrowband wavelength, identifying and locating the specific spectral components or spatial regions causing speckle problems. This powerful diagnostic capability is completely unavailable in existing standard measurement methods. It can greatly accelerate the iterative development of speckle suppression technology in laser display systems, providing an unprecedentedly powerful tool for technological advancement in the industry. Attached Figure Description

[0051] Figure 1 This is a flowchart of the color speckle measurement method in Example 1.

[0052] Figure 2 This is a schematic diagram of the structure of Example 2.

[0053] Figure 3 This is a schematic diagram of the structure of Example 3. Detailed Implementation

[0054] Example 1

[0055] As an embodiment of the present invention, a method for measuring color speckle is disclosed. This method is based on spatial light modulation (SLM) technology to quantify and characterize color speckle phenomena in laser display systems. See also... Figure 1 As shown, the steps of this measurement method include:

[0056] Step a): An image of a target surface exhibiting a colored speckle pattern is projected onto the modulation plane of a spatial light modulator using an imaging module;

[0057] Step b): Divide the modulation plane into multiple spatial regions, select the spatial regions in sequence, and guide the light signal of the selected spatial region into a dispersive element for spectral dispersion. Then, a first image sensor collects the spectral data after dispersion until the spectral data of all spatial regions on the modulation plane are collected.

[0058] Step c): Reconstruct the acquired spectral data into a three-dimensional hyperspectral data cube containing spatial and spectral dimensions based on its corresponding spatial location information. ;

[0059] Step d): Based on the three-dimensional hyperspectral data cube By combining a preset chromaticity matching function or a filter spectral response curve, at least one of the following speckle measurement indicators is calculated and output: luminance speckle contrast, luminance histogram, variance of color speckle based on CIE1976 chromaticity diagram, covariance of color speckle, and color speckle distribution map.

[0060] This invention utilizes a spatial light modulator as a programmable spatial selector, and selects different regions of the target image's light signal through electronic control, realizing a completely non-mechanical spatial scanning. This avoids a series of problems introduced by mechanical motion, such as vibration, positioning error, wear, and speed limitations, in traditional push-broom hyperspectral instruments or optical measurement devices with filter wheels.

[0061] Furthermore, to make the image acquired by the first image sensor clearer, step a) further includes a sharpness adjustment step. Specifically, the image captured by the imaging lens of the imaging module is divided into a main optical path and an auxiliary optical path by a beam splitting system. The main optical path is imaged onto the modulation plane, and the auxiliary optical path is imaged onto a second image sensor. The sharpness score of the image formed by the second image sensor is calculated, and the imaging lens is adjusted using the sharpness score to make the image on the modulation plane clearer. This step is implemented by the control and processing module. After the second image sensor receives the image formed by the auxiliary optical path, it transmits it to the control and processing module, which calculates the sharpness score. The specific calculation method for the sharpness score is conventional technology in the art and will not be elaborated here. After the control and processing module calculates the sharpness score, it adjusts the focal length of the imaging lens. The focused imaging lens then re-images on the second image sensor, and the control and processing module calculates the sharpness score again. If the sharpness score does not meet the requirements, the focal length of the imaging lens is repeatedly adjusted until the sharpness score meets the requirements. Preferably, the adjustment of the imaging lens is stopped when the sharpness score reaches the maximum value.

[0062] This embodiment achieves clear imaging by adjusting the focal length of the imaging lens. The optical path is divided into a main optical path and an auxiliary optical path by a beam-splitting system, both capable of simultaneous imaging. This allows for real-time adjustment of image sharpness, improving the accuracy of speckle measurement. Furthermore, to ensure clear imaging from the first image sensor, the beam-splitting system splits the main and auxiliary optical paths in a 9:1 ratio. A larger proportion of the light is used for imaging to facilitate subsequent calculations and obtain more accurate measurement results, while a smaller proportion is used to adjust the focal length of the imaging lens. The auxiliary optical path only requires the second image sensor to clearly acquire the image, which can then be analyzed by the control and processing module, resulting in a clearer image and further improving measurement accuracy.

[0063] In step b), to enable the regionally distributed optical signal delivery to the dispersive element, this embodiment employs a digital micromirror array (DMI) as a spatial light modulator. The DMI consists of thousands of micromirrors, each of which can be independently deflected to an "on" state (e.g., +12°) or an "off" state (e.g., -12°) under the command of the control and processing module. At the start of the measurement, the control and processing module executes a scanning sequence; for example, it first sets the first row of micromirrors in the DMI array to the "on" state, while setting all other micromirrors to the "off" state. Micromirrors in the "on" state reflect the optical signal of the corresponding spatial region to the dispersive element. The deflection of micromirrors to the "on" and "off" states is prior art and will not be elaborated upon here.

[0064] In step b), the spatial light modulator selects the spatial regions sequentially, either row-by-row or column-by-column, until all spatial regions within the modulation plane have been selected. This row-by-row or column-by-column selection method facilitates control over the switching of spatial regions and minimizes the chance of missing micromirrors, ensuring the image formed by the imaging lens is completely transmitted to the dispersive element.

[0065] Following step c), the method further includes at least one calibration step among radiance calibration, spectral calibration, and geometric calibration of the three-dimensional hyperspectral data cube, thereby obtaining a more accurate three-dimensional hyperspectral data cube and helping to further improve the accuracy of speckle measurement.

[0066] Specifically, the specific operations for spectral calibration, radiance calibration, and geometric calibration of the three-dimensional hyperspectral data cube are as follows:

[0067] Spectral calibration: Spectral calibration aims to determine the accuracy of the three-dimensional data cube in the spectral dimension, that is, to determine the pixel coordinates on the first image sensor relative to the physical wavelength. The correspondence between them is established. For example, a spectral calibration light source with a known characteristic peak wavelength (such as a mercury-argon lamp, krypton lamp, or a monochromator with a known output wavelength) is placed in front of the imaging lens. The main control system controls the spatial light modulator to conduct the central region, so that the calibration light shines on the first image sensor through the dispersive element. The data processing unit extracts the pixel position index of the corresponding characteristic peak on the first image sensor and uses the least squares method to fit a polynomial mapping function (usually a quadratic or cubic polynomial) between the pixel index and the wavelength. When reconstructing the three-dimensional data cube, an accurate center wavelength value is assigned to each spectral channel according to this mapping function.

[0068] Radiance calibration: Radiance calibration aims to establish the relationship between the digital grayscale value (DN value) output by the instrument and the actual physical radiance (e.g., ...). The quantitative relationship between the two was determined, and the effects of sensor dark current and optical path vignetting were eliminated. The calibration process is as follows: First, a dark noise image of the first image sensor was acquired in a completely dark environment. Secondly, a standard uniform radiation source (such as an integrating sphere light source traceable to national standards) is used to fill the field of view of the imaging lens to acquire the bright field response image of the system. Due to the output radiance of the integrating sphere It is known that the data processing unit calculates the absolute radiation response coefficient matrix of the system. In actual measurements, for the raw spectral data collected... The data is calibrated to absolute radiance using the following formula. .

[0069] Geometric calibration: Geometric calibration is used to correct spatial position deviations caused by imaging lens distortion and assembly errors between the spatial light modulator and the sensor. During calibration, a high-precision geometric calibration board (e.g., a checkerboard calibration board or a dot matrix calibration board) is placed on the target surface. The main control system acquires images of the calibration board, and the data processing unit identifies the actual image coordinates of the feature points on the calibration board and compares them with the ideal coordinates to calculate the geometric distortion correction model. This is then used to reconstruct the 3D data cube. During the process, this distortion correction model is applied to the spatial dimension. Resampling and interpolation are performed to ensure the geometric accuracy of the measurement results.

[0070] Step d) includes calculating the XYZ tristimulus values, and then calculating the speckle measurement index based on the XYZ tristimulus values. The XYZ tristimulus values ​​are important data for calculating speckle measurement indexes such as luminance speckle contrast, variance, and covariance of color speckle. In this embodiment, the XYZ tristimulus values ​​are obtained from three-dimensional hyperspectral data. The calculation involves precisely calculating the XYZ tristimulus values ​​for each spatial pixel (x, y) in a three-dimensional hyperspectral data cube by performing a weighted integral of its spectral radiance data, thereby generating... , , Three two-dimensional images. That is, the XYZ tristimulus values ​​are represented by two-dimensional images. , , The calculation formula is as follows:

[0071]

[0072]

[0073]

[0074] in, This represents the color matching function of the CIE 1931 standard; (x, y) represents the spatial pixel.

[0075] The calculation method for the speckle measurement index includes at least one of the following:

[0076] The brightness speckle contrast:

[0077] Represents the brightness speckle contrast. Represents spatial standard deviation, Represents the spatial average;

[0078] because The image represents the brightness distribution perceived by the human eye; therefore, brightness speckle contrast... Spatial standard deviation of all pixel values ​​in the image Spatial average The ratio is determined.

[0079] Photometric speckle distribution: statistics The distribution of pixel values ​​in the image is used to generate a luminance histogram, which is used to represent the speckle distribution of luminance.

[0080] The variance and covariance of the colored speckle: First, , , The image is converted pixel by pixel to CIE 1976 u'v' chromaticity coordinates, resulting in... and The conversion formula for two chroma images is:

[0081]

[0082]

[0083] Then according to and Image, calculate the variance of colored speckle. , Covariance :

[0084]

[0085]

[0086]

[0087] in This represents calculating the spatial average value over all pixels in an image;

[0088] Color speckle distribution diagram: Plotting pixels on the CIE 1976 chromaticity diagram The scatter distribution.

[0089] Using this measurement method, the system can ultimately output all quantitative values ​​and visualization charts that conform to the IEC 62906-5-4 standard, ensuring compatibility and comparability with existing testing methods.

[0090] Benefiting from the inherent advantages of hyperspectral data, this invention also provides enhanced analysis capabilities that are unattainable by traditional methods. The data processing unit can utilize the CIE 1931 standard color matching function. Monochromatic speckle images of arbitrary narrowband wavelengths (e.g., the 638nm spectral line of a specific red laser) are extracted from the data cube, and their monochromatic speckle contrast is calculated using the method described in GB / T43590.502. Alternatively, by performing ergonomic calculations across all wavelengths, the system can generate a spectral distribution curve of "speckle contrast vs. wavelength". This curve can precisely identify which one or more specific wavelengths of light source contribute the most to the overall color speckle, providing an unprecedented, root-cause diagnostic tool for the research and development and quality control of laser display devices.

[0091] Example 2

[0092] This embodiment provides a measuring device for implementing the color speckle measurement method described in the above embodiment. The measuring device includes:

[0093] An imaging module, including an imaging lens, is used to image a target surface that presents a color speckle pattern;

[0094] A spatial light modulator is disposed in the main optical path. The modulation plane of the spatial light modulator is used to receive the main beam imaged by the imaging lens and to perform spatial light modulation on the image of the target surface so as to sequentially conduct the light signal of the image in different regions.

[0095] A beam control element is disposed in the imaging module and the space, for receiving the main beam from the imaging module and controlling the polarization, direction, displacement and rotation of the main beam;

[0096] A dispersive element is used to receive the optical signal transmitted from the spatial light modulator and disperse it according to wavelength;

[0097] A first image sensor is used to detect the spectral signal after dispersion by the dispersive element;

[0098] The main control system includes a control unit and a data processing unit. The control unit is used to control the spatial light modulator to divide its modulation plane into multiple spatial regions, and sequentially turn on each of the spatial regions, and synchronously control the first image sensor to perform exposure and data acquisition. The data processing unit is connected to the first image sensor and the control unit, and is configured to: reconstruct a three-dimensional hyperspectral data cube based on a series of spectral signals acquired by the first image sensor, and calculate and output at least one of the color speckle measurement indicators by combining a preset color matching function or filter spectral response curve.

[0099] To enable real-time adjustment of the imaging focal length, the measuring device includes a beam splitting system and a focusing module. The beam splitting system is located behind the imaging lens and is used to split the imaging beam formed by the imaging module into a main optical path and an auxiliary optical path. The focusing module includes a second image sensor located in the auxiliary optical path, used to acquire an image of the target surface to assist focusing. The photosensitive plane of the second image sensor and the modulation plane of the spatial light modulator are located at the image side of the equivalent optical path. The second image sensor is connected to the control unit and the data processing unit. The data processing unit is also used to process the image from the second image sensor and calculate the sharpness score of the image. The control unit is also used to adjust the focal length of the imaging lens according to the sharpness score.

[0100] This embodiment uses a total internal reflection prism as the beam control element and a digital micromirror array as the spatial light modulator to achieve compact and efficient optical path control, as shown in the following structure. Figure 2 As shown.

[0101] In this embodiment, the beam control element is a total internal reflection prism. In other embodiments, the beam control element may also be a mirror, a lens, or a polarization control element.

[0102] The overall workflow of this measuring device is as follows:

[0103] Imaging and Spectroscopy: Light rays from the surface of the target object are first converged and imaged by imaging lens 1. Imaging lens 1 is an electrically controlled lens with electrically adjustable focus and aperture, driven by main control system 10. Main control system 10 includes a control unit and a data processing unit, used to control the imaging lens and process relevant data of the image formed by the imaging lens. The imaging beam then enters spectroscopy system 21, which in this embodiment is a spectroscopic prism cube. It splits the incident beam into two beams at a certain ratio (e.g., 9:1). The beam with the higher ratio enters the digital micromirror array as the main beam, and the beam with the lower ratio enters the second image sensor 3 as the auxiliary beam.

[0104] Auxiliary optical path: The auxiliary beam is directly reflected to the second image sensor 3. The second image sensor 3 and the modulation plane of the digital micromirror array 51 are optically positioned at the image side of the equivalent optical path. The main control system 10 continuously receives real-time images from the second image sensor 3 and transmits them to the data processing unit 9. The data processing unit 9 runs a sharpness evaluation function (e.g., the Tenengrad gradient algorithm) on the received images in real time to calculate a quantized sharpness score. Based on this score, the main control system 10 drives the imaging lens 1 to perform fine adjustments until the sharpness score reaches its peak value. This process ensures that the image on the modulation plane of the digital micromirror array 51 is the sharpest in the main optical path, laying the foundation for subsequent high-precision measurements.

[0105] Main optical path: After the main beam exits from the beam splitting system 21, it enters the total internal reflection prism 41, which serves as the beam control element. The beam is incident on the inner inclined surface of the total internal reflection prism 41 at a specific angle greater than the critical angle of total internal reflection (e.g., 45 degrees), and total internal reflection occurs. The reflected beam is precisely guided to the modulation plane of the digital micromirror array 51.

[0106] Spatial light modulation: The digital micromirror array 51 consists of thousands of micromirrors, and the array plane forms the modulation plane. Each micromirror can be independently deflected to an "on" state (e.g., +12°) or an "off" state (e.g., -12°) under the command of the main control system 10. At the start of the measurement, the main control system 10 executes a scanning sequence. For example, it first sets the first row of micromirrors in the digital micromirror array to the "on" state, while setting all other micromirrors to the "off" state. The micromirrors in the "on" state reflect the light signal of the corresponding spatial region back to the total internal reflection prism 41.

[0107] Optical path separation and dispersion: The light signal reflected from the digital micromirror array 51 is now incident on the inner inclined surface of the total internal reflection prism 41 at an angle close to the normal. Since the total internal reflection condition is no longer met, the light signal will directly penetrate the total internal reflection prism 41 and enter the subsequent dispersive element 6. In this embodiment, the dispersive element 6 is a high-dispersion prism; in other embodiments, the dispersive element can be a diffraction grating. The dispersive element 6 spreads the received light signal along wavelengths, forming a spectral band.

[0108] Spectral Acquisition and Data Processing: After being focused by the collimating lens 7, the spectral band is completely acquired by the first image sensor 8. The main control system 10 then instructs the digital micromirror array 51 to set the first row of micromirrors to the "off" state and the second row of micromirrors to the "on" state, repeating the above process until all spatial rows have been scanned and acquired. That is, in this embodiment, the digital micromirror array selects spatial regions row by row; in other embodiments, column by column selection can also be used. The data processing unit 9 reconstructs all the acquired spectral data according to their corresponding spatial row numbers, ultimately generating a complete three-dimensional hyperspectral data cube, and calculates all color speckle evaluation indicators based on this.

[0109] Alternatively, the second image sensor and the first image sensor may be selected from CMOS, CCD and InGaAs sensors, respectively.

[0110] Example 3

[0111] This embodiment provides another measuring device for implementing the color speckle measurement method described in the above embodiments. The difference between this embodiment and Embodiment 1 is that the beam splitting system in this embodiment uses a polarizing beam splitter prism, and the spatial light modulator uses a silicon-based liquid crystal, with the pixel array plane of the silicon-based liquid crystal 52 forming the modulation plane of the spatial light modulator. The core of this embodiment lies in modularizing the system functions to achieve flexible and efficient color speckle measurement. Its overall structure is as follows: Figure 3 As shown.

[0112] In this embodiment, the overall workflow of the device is as follows:

[0113] Imaging and Spectroscopy: Light rays from the surface of the target object are first converged and imaged by imaging lens 1. Imaging lens 1 is an electronically controlled lens whose focal point can be driven by the main control system 10. The imaged beam then enters the spectroscopy system 22, which consists of a polarizing beam splitter prism. It splits the incident beam into two paths: one beam is transmitted into the main optical path, and the other beam is reflected into the auxiliary optical path.

[0114] Auxiliary optical path: The first beam reflected by the beam splitting system 22 is received by the second image sensor 3. The photosensitive plane of the second image sensor 3 and the pixel array plane of the silicon-based liquid crystal 52 in the main optical path are optically at the image side of the equivalent optical path. The main control system 10 continuously receives the real-time image from the second image sensor 3 and transmits it to the data processing unit 9. The data processing unit 9 runs a sharpness evaluation function (e.g., the Tenengrad gradient algorithm) on the received image in real time to calculate a quantized sharpness score. Based on this score, the main control system 10 drives the imaging lens 1 to perform fine adjustments until the sharpness score reaches its peak value. This process ensures that the image on the pixel array plane of the silicon-based liquid crystal 52 is the sharpest in the main optical path, laying the foundation for subsequent high-precision measurements.

[0115] Main optical path: The main beam transmitted through the beam splitting system 22 enters the second polarizing beam splitter 42, which serves as the optical path guiding and separating element. The main beam is reflected by its inner inclined surface and is precisely guided onto the pixel array plane of the silicon liquid crystal 52.

[0116] Spatial light modulation: The silicon-based liquid crystal 52 acts as a spatial light modulator, and its pixel array can be set to either "on" or "off" state under the command of the main control system 10. At the start of the measurement, the main control system 10 executes a scanning sequence. For example, it first sets the first row of pixels in the pixel array plane of the silicon-based liquid crystal 52 to the "on" state, while setting all other pixels to the "off" state. The pixels in the "on" state will reflect the light signal of the corresponding spatial region back to the second polarization beam splitter 42 after changing its polarization state.

[0117] Optical path separation and dispersion: The signal light reflected from the silicon-based liquid crystal 52, due to its rotated polarization state, will directly pass through the second polarizing beam splitter 42 upon returning, thus separating it from the incident light path. This signal beam then enters the dispersive element 6. In this embodiment, the dispersive element 6 is a high-dispersion prism that spreads the received signal light (representing a spatial row) along wavelengths, forming a spectral band.

[0118] Spectral Acquisition and Data Processing: After being focused by the collimating lens 7, the spectral band is completely acquired by the first image sensor 8. The main control system 10 then instructs the silicon-based liquid crystal 52 to set the first row of pixels to the "off" state and the second row of pixels to the "on" state, and simultaneously triggers the first image sensor 8 to acquire data. This process is repeated until all spatial rows have been scanned and acquired. The data processing unit 9 reconstructs all the acquired spectral data according to their corresponding spatial row numbers, ultimately generating a complete three-dimensional hyperspectral data cube, and calculates all color speckle evaluation indicators based on this cube.

Claims

1. A method for measuring color speckle, characterized in that, Includes the following steps: Step a): An image of a target surface exhibiting a colored speckle pattern is projected onto the modulation plane of a spatial light modulator using an imaging module; Step b): Divide the modulation plane into multiple spatial regions, select the spatial regions in sequence, and guide the light signal of the selected spatial region into a dispersive element for spectral dispersion. Then, a first image sensor collects the spectral data after dispersion until the spectral data of all spatial regions on the modulation plane are collected. Step c): The collected spectral data is reconstructed into a three-dimensional hyperspectral data cube containing spatial and spectral dimensions based on its corresponding spatial location information. ; Step d): Based on the three-dimensional hyperspectral data cube By combining a preset chromaticity matching function or a filter spectral response curve, at least one of the following speckle measurement indicators is calculated and output: luminance speckle contrast, luminance speckle distribution, variance of color speckle based on the CIE1976 chromaticity diagram, covariance of color speckle, and color speckle distribution map.

2. The method for measuring color speckle according to claim 1, characterized in that: Step a) further includes: the image captured by the imaging lens of the imaging module is divided into a main optical path and an auxiliary optical path by a beam splitting system, the main optical path is imaged on the modulation plane, the auxiliary optical path is imaged on the second image sensor, the sharpness score of the image formed by the second image sensor is calculated, and the imaging lens is adjusted using the sharpness score to make the image on the modulation plane clear.

3. The method for measuring color speckle according to claim 1, characterized in that: In step b), the spatial light modulator selects the spatial regions sequentially by selecting row by row or column by column until all the spatial regions within the modulation plane have been selected.

4. The method for measuring color speckle according to claim 1, characterized in that: Step c) includes at least one calibration step among radiance calibration, spectral calibration and geometric calibration of the three-dimensional hyperspectral data cube.

5. The method for measuring color speckle according to any one of claims 1 to 4, characterized in that: Step d) includes calculating the XYZ tristimulus values, and then calculating the speckle measurement index based on the XYZ tristimulus values. The tristimulus values ​​are obtained through a two-dimensional image. , , The calculation formula is as follows: in, This represents the color matching function of the CIE 1931 standard; (x, y) represents the spatial pixel.

6. The method for measuring color speckle according to claim 5, characterized in that: The calculation method for the speckle measurement index includes at least one of the following: The brightness speckle contrast: Represents the brightness speckle contrast. Represents spatial standard deviation, Represents the spatial average; The speckle distribution of the photometric speckle; statistics The distribution of pixel values ​​in the image is used to generate a luminance histogram to represent the speckle distribution. The variance and covariance of the colored speckle: , , The image is converted pixel by pixel to CIE1976 u'v' chromaticity coordinates to obtain and The conversion formula for two chroma images is: Then according to and Image, calculate the variance of colored speckle. , Covariance : in This represents calculating the spatial average value over all pixels in an image; Color speckle distribution diagram: Plotting pixels on the CIE 1976 chromaticity diagram The scatter distribution.

7. A color speckle measuring device, characterized in that: The measuring device is used to implement the color speckle measurement method according to any one of claims 1-6, and the measuring device comprises: An imaging module, including an imaging lens, is used to image a target surface that presents a color speckle pattern; A spatial light modulator is disposed in the main optical path. The modulation plane of the spatial light modulator is used to receive the main beam imaged by the imaging lens and to perform spatial light modulation on the image of the target surface so as to sequentially conduct the light signal of the image in different regions. A beam control element is disposed in the imaging module and the space, for receiving the main beam from the imaging module and controlling the polarization, direction, displacement and rotation of the main beam; A dispersive element is used to receive the optical signal transmitted from the spatial light modulator and disperse it according to wavelength; A first image sensor is used to detect the spectral signal after dispersion by the dispersive element; The main control system includes a control unit and a data processing unit. The control unit is used to control the spatial light modulator to divide its modulation plane into multiple spatial regions, and sequentially turn on each of the spatial regions, and synchronously control the first image sensor to perform exposure and data acquisition. The data processing unit is connected to the first image sensor and the control unit, and is configured to: reconstruct a three-dimensional hyperspectral data cube based on a series of spectral signals acquired by the first image sensor, and calculate and output at least one of the color speckle measurement indicators by combining a preset color matching function or filter spectral response curve.

8. A color speckle measuring device according to claim 7, characterized in that: The measuring device includes a beam splitting system and a focusing module: the beam splitting system is disposed after the imaging lens and is used to split the imaging beam formed by the imaging module into a main optical path and an auxiliary optical path; the focusing module includes a second image sensor disposed in the auxiliary optical path, used to acquire an image of the target surface to assist focusing, the photosensitive plane of the second image sensor and the modulation plane are located at the image side of the equivalent optical path, the second image sensor is connected to the control unit and the data processing unit, the data processing unit is also used to process the image from the second image sensor and calculate the sharpness score of the image, and the control unit is also used to adjust the focal length of the imaging lens according to the sharpness score.

9. A color speckle measuring device according to claim 8, characterized in that: The first image sensor and the second image sensor are any one of CMOS, CCD and InGaAs sensors, respectively.

10. A color speckle measuring device according to claim 7, characterized in that: The spatial light modulator is a digital micromirror array or a liquid crystal on silicon, wherein the micromirror array plane of the digital micromirror array forms the modulation plane, and the pixel array plane of the liquid crystal on silicon forms the modulation plane; and / or, The beam control element is a total internal reflection prism, a mirror, a lens, or a polarization control element; and / or, The dispersive element is a diffraction grating or a high-dispersion prism.

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