A method and system for detecting visible light brightness of a camera

Abstract

The present invention relates to the technical field of image processing camera metering, and in particular to a method and system for detecting visible light brightness of a camera. The method comprises the following steps: obtaining first brightness information of a scene within the camera's field of view when a linear polarizer is in a first transmission direction in a target scene photographed by the camera through a transparent medium, and obtaining second brightness information of the scene within the camera's field of view when the linear polarizer is in a direction different from the first transmission direction; based on the first brightness information and the second brightness information, analyzing characteristics of brightness changes with changes in the transmission direction of the linear polarizer to distinguish between light reflected from the surface of the transparent medium and light transmitted from the target scene, so as to determine the contribution of light reflected from the surface of the transparent medium to the total brightness; and accurately determining the brightness of the target scene by analyzing characteristics of brightness changes with the transmission direction of the polarizer.

Description

Technical Field

[0001] The present invention relates to the field of image processing technology, and in particular to a method and system for detecting visible light brightness of a camera. Background Art

[0002] In many practical applications, cameras often need to capture images through transparent media. However, when a camera captures through a transparent medium, the light received by the image sensor not only comes from the target scene on the other side of the transparent medium (effective transmitted light), but also includes interference light from the camera's own environment and reflected back from the surface of the transparent medium. When the lighting conditions in the camera's environment differ significantly from those of the target scene, such as a bright room with a dim window outside, or a well-lit exhibition hall with localized lighting inside a display case, reflections from the transparent medium's surface can seriously interfere with the camera's brightness detection. Images formed by light sources or high-brightness objects in the camera's environment reflected from the transparent medium's surface will overlap with the image of the target scene, entering the camera and being captured together.

[0003] Existing camera metering systems, regardless of the metering mode (e.g., global average, center-weighted, or zoned), are based on analyzing the intensity of light entering the lens. Consequently, when calculating the brightness of the metered area, these systems are unable to intelligently distinguish between the effective transmitted light from the target scene and the interfering light reflected from transparent surfaces (including irregularities). The resulting brightness value is the combined total intensity of these two light sources.

[0004] When the ambient brightness on the camera side is significantly higher than the target scene brightness, or when the reflectivity of a transparent medium is high, or when there are strong reflective defects on the surface, the contribution of reflected light to the metering reading will become significant, and may even dominate the metering result. Especially when the metering area covers these highly reflective areas, the brightness value in that area will be significantly inflated.

[0005] If the camera's automatic exposure algorithm fails to effectively identify and compensate for the additional brightness introduced by the reflection from the transparent medium's surface, it will make exposure decisions based on the brightness detection results that are biased higher due to interference from the reflected light. If the primary shooting intention is to clearly capture the target scene on the other side of the transparent medium, the automatic exposure control unit will erroneously determine that the image is too bright and subsequently reduce the exposure (such as shortening the shutter time, reducing the aperture, and lowering the sensitivity). As a result, although the reflected bright spot may no longer be overexposed, the target scene that actually needs to be recorded becomes dim due to underexposure, and a large amount of detail, color, and morphological information is lost, resulting in a serious degradation of the final image quality, which cannot meet the image acquisition requirements of specific application scenarios. The root cause of this problem is that existing visible light brightness detection methods fail to effectively separate the transmitted light of the target scene from the reflected light from the transparent medium interface for independent evaluation.

[0006] In view of the above problems, the existing technology needs to be improved urgently. Summary of the Invention

[0007] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a method and system for detecting visible light brightness of a camera.

[0008] In a first aspect, the present invention provides a method for detecting visible light brightness of a camera, the method comprising the following steps:

[0009] S1: Acquire first brightness information of a scene within the camera's field of view when the linear polarizer is in a first transmission direction when the camera photographs a target scene through a transparent medium, and obtain second brightness information of the scene within the camera's field of view when the linear polarizer is in a direction different from the first transmission direction;

[0010] S2: Based on the first brightness information and the second brightness information, analyzing characteristics of brightness changes as the transmission direction of the linear polarizer changes, so as to distinguish between the portion of light reflected by the surface of the transparent medium and the portion of light transmitted by the target scene, and thereby determining the contribution of the light reflected by the surface of the transparent medium to the total brightness;

[0011] S3: Based on the contribution of the reflected light on the surface of the transparent medium to the total brightness, correct at least one of the first brightness information and the second brightness information or a combination thereof to obtain a target brightness representing the target scene on the other side of the transparent medium.

[0012] In step S1 of the present application, scene brightness information captured by a camera under at least two different linear polarizer transmission directions is obtained. Light reflected from a transparent surface typically exhibits polarization characteristics, while light from the target scene may exhibit different polarization states. Obtaining brightness data under different polarization directions provides a basis for subsequent analysis of the polarization characteristics of the scene light. Step S2, based on the brightness information obtained under different polarization directions in step S1, analyzes the variation in brightness with polarization direction. This variation reflects the distribution of polarized light in the scene. By analyzing the polarization characteristics, the method can identify and distinguish between light reflected from the transparent surface and light transmitted from the target scene. Furthermore, the method calculates the contribution of the reflected light to the total measured brightness. This process identifies and quantifies interfering light (reflected light). Step S3 uses the reflected light contribution determined in step S2 to correct the initial brightness information obtained in step S1. By removing the reflected light contribution, the corrected brightness information represents the brightness of the target scene on the other side of the transparent medium. This process provides the target scene brightness without the influence of reflections, resolving the issue of original brightness measurements containing reflection interference.

[0013] In a second aspect, a visible light brightness detection system for a camera is provided, the system comprising:

[0014] Polarization information acquisition module: acquires first brightness information of the scene in the camera's field of view when the linear polarizer is in a first transmission direction when the camera photographs the target scene through a transparent medium, and obtains second brightness information of the scene in the camera's field of view when the linear polarizer is in a direction different from the first transmission direction;

[0015] a characteristic analysis and identification module for analyzing, based on the first brightness information and the second brightness information, characteristics of brightness changes as the transmission direction of the linear polarizer changes, so as to distinguish between the portion of light reflected by the surface of the transparent medium and the portion of light transmitted by the target scene, and thereby determine the contribution of the light reflected by the surface of the transparent medium to the total brightness;

[0016] A brightness correction module is configured to correct at least one of the first brightness information and the second brightness information or a combination thereof based on the contribution of the reflected light on the surface of the transparent medium to the total brightness, so as to obtain a target brightness representing the target scene on the other side of the transparent medium.

[0017] Compared with the prior art, the present invention has the following beneficial effects:

[0018] By acquiring brightness information under different polarization directions, analyzing the brightness change characteristics, distinguishing reflected light from transmitted light, and performing corrections, it is possible to distinguish the light reflected from the surface of the transparent medium from the transmitted light of the target scene, determine the contribution of the light reflected from the surface of the transparent medium to the total brightness, and obtain the brightness of the target scene. BRIEF DESCRIPTION OF THE DRAWINGS

[0019] Figure 1 Flowchart of the present invention.

[0020] Figure 2 It is a structural diagram of the present invention.

[0021] In the figure: 201, polarization information acquisition module; 202, characteristic analysis and identification module; 203, brightness correction module. DETAILED DESCRIPTION

[0022] The embodiments of the present invention are described in detail below, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and are not to be construed as limiting the present invention.

[0023] The terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature specified as "first" or "second" may explicitly or implicitly include one or more of the specified features. In the description of the present invention, "plurality" means two or more, unless otherwise specifically defined.

[0024] Application scenario: How to solve the technical problem that existing visible light brightness detection methods are unable to effectively distinguish and suppress the transmitted light of the target scene and the interference light reflected back from the surface of the transparent medium, including specular reflections and irregular strong reflections. As a result, the metering results are generally inflated by the interference light, which in turn causes the automatic exposure system to erroneously reduce the exposure. Ultimately, the target subject on the other side of the transparent medium is severely underexposed, resulting in a large amount of loss of image details and color information, and failing to meet the image acquisition quality requirements in specific scenarios.

[0025] like Figure 1 A method for detecting visible light brightness of a camera is shown, the method comprising the following steps:

[0026] S1: Acquire first brightness information of a scene within the camera's field of view when the linear polarizer is in a first transmission direction when the camera photographs a target scene through a transparent medium, and obtain second brightness information of the scene within the camera's field of view when the linear polarizer is in a direction different from the first transmission direction;

[0027] S2: Based on the first brightness information and the second brightness information, analyzing the characteristics of brightness changes as the transmission direction of the linear polarizer changes, so as to distinguish the portion of light reflected by the transparent medium surface from the portion of light transmitted by the target scene, and thereby determine the contribution of the light reflected by the transparent medium surface to the total brightness;

[0028] S3: Based on the contribution of the reflected light on the surface of the transparent medium to the total brightness, correct at least one of the first brightness information and the second brightness information or a combination thereof to obtain a target brightness representing the target scene on the other side of the transparent medium.

[0029] Step S1 acquires scene brightness information captured by the camera under at least two different linear polarizer transmission directions. Light reflected from a transparent surface typically exhibits polarization characteristics, while light from the target scene may exhibit different polarization states. Obtaining brightness data under different polarization directions provides a foundation for subsequent analysis of the polarization characteristics of the scene light.

[0030] Step S2 analyzes the brightness variation with polarization direction based on the brightness information obtained in step S1 for different polarization directions. This variation reflects the distribution of polarized light in the scene. By analyzing the polarization characteristics, the method can identify and distinguish between light reflected from the transparent surface and light transmitted from the target scene. Furthermore, the method calculates the contribution of the reflected light to the total measured brightness. This process enables the identification and quantification of interfering light (reflected light).

[0031] Step S3 uses the reflected light contribution determined in step S2 to correct the initial brightness information obtained in step S1. By removing the reflected light contribution, the corrected brightness information represents the brightness of the target scene on the other side of the transparent medium. This process provides the target scene brightness without the influence of reflections, resolving the problem of reflection interference in the original brightness measurement.

[0032] Specifically, when a camera captures a target scene through a transparent medium, reflected light is generated from the surface of the transparent medium. This reflected light, combined with the transmitted light from the target scene, constitutes the total light signal received by the camera. Existing brightness detection methods cannot distinguish between these two types of light, resulting in an overestimation of the measured total brightness, which affects subsequent exposure control. This method uses a linear polarizer and modifies its transmission direction to obtain scene brightness information under different polarization states. Since the reflected light from the transparent surface typically has distinct polarization characteristics, while the polarization characteristics of the transmitted light from the target scene may differ, by comparing the brightness differences under at least two different polarization directions, the polarization characteristics of different regions in the scene can be analyzed. Based on this polarization characteristic analysis, the method can identify regions primarily contributed by light reflected from the transparent surface and those primarily contributed by light transmitted from the target scene. Furthermore, the method quantifies the specific contribution of light reflected from the transparent surface to the total brightness. Finally, the calculated reflected light contribution is used to correct the original measured brightness information, for example by subtracting the reflected light contribution, thereby obtaining a more accurate brightness value representing the target scene on the other side of the transparent medium. Therefore, this method effectively separates and suppresses the interference of reflected light from the surface of the transparent medium, obtains information that is closer to the actual target scene brightness, and provides a basis for subsequent accurate automatic exposure control.

[0033] Furthermore, step S2 includes:

[0034] S21: Acquire brightness information collected in different transmission directions, where each brightness information includes first brightness information, second brightness information, and optionally one or more optional brightness information collected in other different transmission directions;

[0035] S22: Calculating polarization characteristic parameters of an area within the camera field of view where brightness changes as the transmission direction of the linear polarizer changes;

[0036] S23: comparing the polarization characteristic parameters calculated in the brightness change region with a typical polarization characteristic parameter range in a preset reference model to generate a comparison result;

[0037] S24: Identify the source of the brightness change based on the comparison result, and distinguish between the portion dominated by the light reflected from the surface of the transparent medium and the portion dominated by the light source or object in the target scene that has its own polarization characteristics;

[0038] S25: Excluding or compensating for the portion of brightness change dominated by the light source or object having polarization characteristics in the target scene, so as to determine the contribution of the light reflected from the surface of the transparent medium to the total brightness.

[0039] Specifically, this method acquires more comprehensive polarization data by acquiring scene brightness information from at least two, and preferably multiple, different transmission directions. Furthermore, using this multi-directional brightness information, polarization parameters, such as the degree of polarization and the direction of the polarization principal axis, are calculated for regions within the camera's field of view where brightness varies with the polarizer's orientation. These parameters quantitatively describe the polarization state of the light. Light reflected from a transparent surface and light emitted by a light source or object with inherent polarization properties in the target scene typically have different polarization parameter ranges. The calculated polarization parameters are compared with a preset reference model that stores the polarization parameter ranges for known sources (such as glass surface reflections and typical naturally polarized sources). Based on the comparison results, the source of the brightness variation is identified, distinguishing which areas are primarily caused by reflection from the transparent surface and which areas are primarily caused by inherently polarized light sources or objects in the target scene. Finally, the brightness variation identified as being caused by the target scene's inherent polarization sources is eliminated or compensated. This means that when calculating the contribution of light reflected from the transparent surface to the total brightness, the effect of the target scene's inherent polarization light is subtracted or adjusted. Therefore, the contribution of the reflected light on the surface of the transparent medium to the total brightness more accurately reflects the influence of the reflected light, eliminates the interference of the polarized light of the target scene itself, and lays the foundation for subsequent accurate brightness correction and obtaining accurate brightness information characterizing the target scene.

[0040] Furthermore, step S22 includes:

[0041] S221: The first brightness information and the second brightness information in step S21, as well as one or more optional brightness information collected in other different transmission directions, are collectively referred to as multi-frame polarization brightness information;

[0042] S222: determining a spatial offset of a corresponding scene area in each frame of brightness information caused by relative displacement or posture change between the camera and the target scene during acquisition of the multiple frames of polarization brightness information;

[0043] S223: performing image registration processing on the multiple frames of polarization brightness information according to the determined spatial offset to generate a set of spatially aligned multiple frames of polarization brightness information, ensuring that each brightness value used to calculate the polarization characteristics of the same scene point in the spatially aligned multiple frames of polarization brightness information corresponds to the same physical area of ​​the target scene;

[0044] S224: Based on the spatially aligned multi-frame polarization brightness information, calculate polarization characteristic parameters of an area where brightness changes along the transmission direction of the linear polarizer within the camera field of view.

[0045] Specifically, this method aims to address the problem of relative motion between the camera and the target scene during the acquisition of multiple frames of polarized brightness information, which can cause positional offsets in the same physical region across different frames. First, step S221 collects multiple frames of brightness information acquired under different linear polarizer transmission directions. Next, step S222 analyzes the content of these brightness information frames to determine the spatial offset of each frame relative to a reference frame. This offset reflects the relative motion of the camera or scene during acquisition. Then, step S223 performs image registration on all brightness information frames based on the determined spatial offsets. Image registration corrects the spatial misalignment between images by applying appropriate geometric transformations (such as translation, rotation, and scaling) to generate a set of spatially aligned images. This process ensures that, in subsequent calculations, brightness values ​​extracted from different frames correspond to the same physical location in the target scene. Finally, step S224 calculates the polarization characteristic parameters of the region within the camera's field of view where brightness varies with the polarizer transmission direction, based on these spatially aligned frames of brightness information. By eliminating data misalignment caused by motion, the calculated polarization characteristic parameters are more accurate, providing a reliable data basis for the subsequent distinction between reflected light and transmitted light.

[0046] Furthermore, the polarization characteristic parameter includes one or a combination of two of the polarization degree and the polarization main axis direction calculated according to the corresponding brightness information.

[0047] Furthermore, step S222 includes:

[0048] S2221: Applying an image structure extraction algorithm to each frame of the multiple frames of polarization brightness information to generate a structural feature map corresponding to the frame of image;

[0049] S2222: Select one frame from the multiple frames of polarization brightness information as a reference frame, and use a structural feature map corresponding to the reference frame image as a reference structural feature map;

[0050] S2223: determining an initial region correspondence relationship by performing a region-based cross-correlation operation or a phase correlation operation between the reference structure feature map and the structure feature maps corresponding to other frame images except the reference frame;

[0051] S2224: Perform consistency check on the determined initial region correspondence, and determine the spatial offset of each frame relative to the reference frame based on the region correspondence that meets the consistency condition.

[0052] Among them, an image structure extraction algorithm is applied to each frame image in the multi-frame polarization brightness information to generate a structural feature map. The structural feature map contains the edge information or gradient direction information of the image, thereby reducing the influence of the scene illumination change independent of the rotation of the polarizer on the pixel intensity in the multi-frame polarization brightness information. One frame in the multi-frame polarization brightness information is selected as the reference frame, and the structural feature map corresponding to the reference frame image is used as the reference structural feature map. Between the reference structural feature map and the structural feature maps corresponding to other frame images except the reference frame, the initial regional correspondence is determined by performing a region-based cross-correlation operation or a phase correlation operation. The determined initial regional correspondence is checked for consistency. Based on the regional correspondence that meets the consistency condition, the spatial offset of each frame relative to the reference frame is determined.

[0053] Specifically, when a camera captures a target scene through a transparent medium and collects multiple frames of polarized brightness information, the relative displacement or posture change of the camera or target scene can cause the position of the same physical region on the image sensor to shift between frames. Direct image alignment based on raw brightness information is susceptible to brightness variations caused by polarizer rotation and changes in scene illumination, resulting in inaccurate matching. To address this issue, this solution applies an image structure extraction algorithm, such as edge detection or gradient calculation, to each raw brightness image frame to generate a structural feature map that reflects the image's geometric structure. These structural feature maps are insensitive to overall brightness variations. One frame is then selected as a reference frame, and its structural feature map is used as a benchmark. Next, initial matching relationships for corresponding regions in the image are found by performing region-based cross-correlation or phase correlation operations between the reference structural feature map and the structural feature maps of the remaining frames. These operations are performed on the structural feature map, effectively reducing the interference of brightness variations on the matching process. The resulting initial region correspondences may contain false matches, so consistency verification is required, for example, by fitting a geometric transformation model and eliminating correspondences that do not conform to the model. Finally, based on the verified, reliable region correspondences that meet consistency requirements, the precise spatial offset of each image frame relative to the reference frame is calculated. This provides the precise spatial offset information required for subsequent image registration, ensuring that the brightness values ​​of different frames correspond to the same physical point in the scene when calculating polarization parameters, thereby improving the accuracy of polarization analysis.

[0054] Furthermore, the structural feature map includes edge information or gradient direction information of the image to reduce the impact of scene illumination changes independent of polarizer rotation on pixel intensity in multi-frame polarization brightness information.

[0055] Among them, the structural feature map contains the edge information or gradient direction information of the image. Edge information can be obtained by applying edge detection algorithms, such as the Canny edge detector or the Sobel operator, which can identify the boundaries of areas where the brightness in the image changes significantly. Gradient direction information can be obtained by calculating the gradient of the image in the horizontal and vertical directions and determining the direction in which the brightness changes fastest at each pixel. Compared with the original pixel brightness value, this information is more robust to changes in the overall or local illumination intensity of the image. As a result, the generated structural feature map can more stably characterize the geometric structural features of the image, which are the basis for determining the relative spatial positions between different frame images.

[0056] Furthermore, step S2224 includes:

[0057] S22241: Extract and match two or more sets of feature point coordinates from multiple frames of polarized brightness images, directly fit the affine transformation matrix using the least squares method, filter out matching points with excessive errors in the initial transformation based on a preset residual threshold, and re-perform the least squares fit on the remaining matching points to obtain the final geometric transformation model;

[0058] S22242: For each of the initial region correspondences, calculate the degree of conformity between the correspondence and the geometric transformation model;

[0059] S22243: Based on the calculated degree of conformity, determine which correspondences in the initial region correspondences satisfy the region correspondences of the consistency condition.

[0060] When a camera captures a target scene through a transparent medium, relative displacement or posture changes between the camera and the target scene may occur, leading to spatial offsets between multiple frames of polarization intensity information acquired at different times. Initial region correspondences determined using region-based cross-correlation or phase correlation operations may contain inaccuracies, affecting the accuracy of the spatial offset determination. To address this issue, this solution introduces a global geometric transformation model based on feature point matching to verify the reliability of the initial region correspondences. First, feature points with unique textures or structures are extracted from the multiple polarization intensity images and matched. For example, feature extraction algorithms such as SIFT, SURF, or ORB can be used, and descriptor matching methods can be used to find corresponding point pairs. Then, using the coordinates of these matched feature points, an affine transformation matrix is ​​fitted using the least squares method to describe the overall spatial transformation between frames. To improve the robustness of the model, an iterative optimization process is used to remove matching points that deviate significantly from the initial model based on a preset residual threshold. The remaining matching points are then used to refit the model to obtain a geometric transformation model that more accurately reflects the overall displacement between frames. This model provides a global and relatively reliable reference for spatial correspondence between frames. Next, the geometric transformation model is used to evaluate each initial region correspondence. For each region correspondence obtained through the region correlation operation, the difference or degree of consistency between the correspondence and the correspondence predicted by the global geometric transformation model is calculated.

[0061] For example, the coordinates of the center point of the region in the reference frame can be calculated, and the position in the current frame predicted by the geometric transformation model, and the distance between the position in the current frame actually determined by the region correspondence can be calculated. Finally, a judgment criterion is set based on the calculated degree of compliance, such as the distance being less than a certain threshold. Only those region correspondences whose degree of compliance reaches the preset standard are considered to be region correspondences that meet the consistency conditions. These region correspondences that are judged to be consistent are then used to determine the precise spatial offset of each frame relative to the reference frame. Through this method, the global geometric model obtained by feature point matching is used as a reference to effectively filter out erroneous correspondences that may occur in region-related operations, ensuring that the region correspondences used to determine the spatial offset are reliable, thereby improving the accuracy of spatial offset calculation and subsequent image registration, and ultimately contributing to more accurate calculation of polarization characteristic parameters.

[0062] Furthermore, step S25 includes:

[0063] S251: monitoring the temporal variation of the polarization characteristic parameter of the brightness variation portion during the process of collecting each brightness information in different transmission directions to obtain temporal variation of the polarization characteristic parameter;

[0064] S252: When the amplitude of the polarization parameter change exceeds a preset threshold, adjusting, based on the temporal change of the obtained polarization characteristic parameters, a strategy or parameters used for excluding or compensating for the portion of brightness change identified as being dominated by a light source or object having its own polarization characteristic in the target scene, to obtain an adjusted exclusion or compensation strategy or parameters;

[0065] S253: Applying the adjusted exclusion or compensation processing strategy or parameters, excluding or compensating for the brightness change portion dominated by the light source or object with its own polarization characteristics in the target scene, and calculating the contribution of the reflected light on the surface of the transparent medium to the total brightness.

[0066] Specifically, while collecting multiple frames of polarization brightness information, the system continuously calculates polarization characteristic parameters for brightness variation areas and records their changes over time. A threshold is then set to detect significant changes in the polarization parameters. When the amplitude of the monitored polarization parameter changes exceeds this threshold, it indicates that the polarization source in the target scene has undergone dynamic changes. Based on the monitored temporal changes in the polarization parameters, such as the amplitude or trend of the change, the system dynamically adjusts the processing strategy or parameters used to exclude or compensate for the influence of the target scene's own polarization source. For example, if the polarization degree decreases significantly, the compensation weight for the polarized light component in that area may need to be reduced. Finally, the adjusted exclusion or compensation strategy or parameters are applied to the brightness changes identified as being dominated by the target scene's own polarization source. This approach allows for more accurate separation of these effects from the overall brightness variation, even if the polarization characteristics of the target scene change over time, allowing for more precise calculation of the contribution of light reflected from the transparent medium to the total brightness. This improves the ability to distinguish between light reflected from the transparent medium and the target scene's own polarized light in complex dynamic scenes, thereby increasing the accuracy of determining the contribution of light reflected from the transparent medium to the total brightness.

[0067] In some specific embodiments, a time window can be set, such as the most recent N-frame multi-frame polarization brightness information acquisition cycle. After each acquisition cycle, the polarization characteristic parameters (e.g., degree of polarization) of the brightness change region are calculated. Step S251 can calculate the degree of polarization sequence of the region within the most recent N cycles. Step S252 can calculate the standard deviation of the degree of polarization sequence or the difference between the maximum and minimum values. If the standard deviation or difference exceeds a preset threshold (e.g., 0.05), it is determined that the polarization characteristics have changed significantly. At this time, the compensation coefficient used to compensate for the influence of the target scene's own polarization light can be adjusted based on the magnitude of the standard deviation or difference. For example, the compensation coefficient can be inversely proportional to the change; the greater the change, the greater the adjustment of the compensation coefficient. Step S253 applies the adjusted compensation coefficient to compensate for the brightness change caused by the target scene's own polarization source identified in the current acquisition cycle, thereby calculating the contribution of the light reflected from the transparent medium surface to the total brightness.

[0068] Furthermore, step S3 includes:

[0069] S31: performing a first correction process on at least one of the first brightness information and the second brightness information, or a combination thereof, based on a contribution of the reflected light on the surface of the transparent medium to the total brightness, to obtain intermediate brightness information in which the influence of the reflected light on the surface of the transparent medium has been reduced;

[0070] S32: Obtaining spectral transmittance characteristics or color characteristic parameters of the transparent medium;

[0071] S33: Based on the acquired spectral transmission characteristics or color characteristic parameters, a second correction process is performed on the intermediate brightness information. The second correction process is used to compensate for the spectral change or intensity attenuation caused by the transparent medium on the transmitted light of the target scene, so as to obtain a target brightness representing the target scene on the other side of the transparent medium.

[0072] The first correction process removes the reflected light component from the original luminance information based on the contribution of reflected light from the transparent medium's surface to the total luminance. This can be achieved by subtracting the calculated reflected light contribution from the total luminance, or by establishing a model to separate the reflected and transmitted light components. Obtaining the spectral transmittance or color characteristic parameters of the transparent medium can be accomplished in a variety of ways, such as measuring the spectral transmittance of the transparent medium during system installation or by consulting a pre-defined optical parameter database based on the type of transparent medium (e.g., ordinary glass, low-iron glass, coated glass, etc.). These parameters can be expressed as transmittance curves at different wavelengths or simplified as a color correction matrix or lookup table that describes color shift and overall attenuation. The second correction process uses these acquired parameters to compensate for the intermediate luminance information after the first correction. If a spectral transmittance curve is acquired, the spectral distribution of the intermediate luminance information can be adjusted based on this curve. If color characteristic parameters are acquired, a corresponding color correction algorithm or lookup table can be applied to compensate for the color shift and luminance attenuation caused by the transparent medium.

[0073] Specifically, this method first uses polarization information analysis to separate the contribution of light reflected from the transparent medium's surface from the total brightness information captured by the camera, which includes both reflected and transmitted light. This separation process identifies the characteristics of brightness variations with polarization direction and distinguishes reflected light from transmitted light of the target scene. Based on this contribution, a first correction process is performed to subtract or compensate for the influence of reflected light from the original brightness information, generating preliminary intermediate brightness information that primarily reflects transmitted light. This step addresses the problem of artificially inflated total brightness caused by interference from reflected light. However, transparent media are not perfectly transparent; they absorb or scatter some light and may attenuate light of different wavelengths differently, thus altering the intensity and color of the transmitted light. Therefore, the spectral transmission or color characteristic parameters of the transparent medium are further obtained. Finally, a second correction process is performed on the intermediate brightness information based on these parameters. This process compensates for the attenuation and spectral changes of the transmitted light caused by the transparent medium, ensuring that the resulting brightness information more accurately reflects the true brightness of the target scene on the other side of the transparent medium. By combining reflected light removal and medium transmission compensation, this method improves the accuracy of determining the target scene's brightness in the presence of transparent medium interference, providing accurate input for subsequent automatic exposure control.

[0074] refer to Figure 2 A visible light brightness detection system for a camera is shown, the system comprising:

[0075] Polarization information acquisition module: acquires first brightness information of the scene in the camera's field of view when the linear polarizer is in a first transmission direction when the camera photographs the target scene through a transparent medium, and obtains second brightness information of the scene in the camera's field of view when the linear polarizer is in a direction different from the first transmission direction;

[0076] Characteristic Analysis and Identification Module: Based on the first brightness information and the second brightness information, analyzes the characteristics of brightness changes as the transmission direction of the linear polarizer changes, so as to distinguish the portion of light reflected by the transparent medium surface from the portion of light transmitted by the target scene, and determine the contribution of the light reflected by the transparent medium surface to the total brightness;

[0077] Brightness correction module: Based on the contribution of the reflected light on the surface of the transparent medium to the total brightness, at least one of the first brightness information and the second brightness information or a combination thereof is corrected to obtain a target brightness representing the target scene on the other side of the transparent medium.

[0078] Specifically, this system addresses the problem of underexposure of the target scene caused by reflected light from the transparent surface interfering with brightness measurement when a camera shoots through a transparent medium, such as a glass window. When a camera shoots through a transparent medium, such as a glass window, the light received by the camera is a mixture of transmitted light from the target scene and light reflected from the transparent surface. When the reflected light is strong, existing brightness measurement methods cannot distinguish between these two types of light, resulting in an overestimated total brightness. If automatic exposure is performed based on this overestimated brightness, the camera will mistakenly reduce the exposure, resulting in underexposure of the target scene. This system incorporates a polarization information acquisition module to acquire scene brightness information in at least two different polarization directions. This information is fed into a characteristic analysis and identification module, which uses the differences in the polarization properties of reflected and transmitted light to analyze how brightness varies with polarization direction. This analysis enables the system to identify and quantify the specific contribution of the reflected light from the transparent surface to the total brightness. The brightness correction module then uses this contribution to correct the original brightness information. For example, the reflected light contribution can be subtracted from the total brightness to obtain information that more closely approximates the true brightness of the target scene. The resulting corrected brightness information accurately represents the brightness of the target scene on the other side of the transparent medium, eliminating interference from reflected light. Automatic exposure control based on this accurate target brightness information ensures proper exposure of the target scene, avoiding underexposure caused by reflection interference, thereby improving image acquisition quality.

[0079] The basic principles, main features, and advantages of the present invention are shown and described above. Those skilled in the art should understand that the present invention is not limited to the above embodiments. The above embodiments and descriptions only describe the principles of the present invention. Various changes and improvements are possible without departing from the spirit and scope of the present invention, and such changes and improvements fall within the scope of the invention as claimed.

Claims

1. A method for detecting visible light brightness of a camera, characterized in that: The method comprises the following steps: S1: Acquire first brightness information of a scene within the camera's field of view when the linear polarizer is in a first transmission direction when the camera photographs a target scene through a transparent medium, and obtain second brightness information of the scene within the camera's field of view when the linear polarizer is in a direction different from the first transmission direction; S2: Based on the first brightness information and the second brightness information, analyzing characteristics of brightness changes as the transmission direction of the linear polarizer changes, so as to distinguish between the portion of light reflected by the surface of the transparent medium and the portion of light transmitted by the target scene, and thereby determining the contribution of the light reflected by the surface of the transparent medium to the total brightness; S3: Based on the contribution of the reflected light on the surface of the transparent medium to the total brightness, correct at least one of the first brightness information and the second brightness information, or a combination thereof, to obtain a target brightness representing the target scene on the other side of the transparent medium; Step S2 includes: S21: Acquire brightness information collected in different transmission directions, where each brightness information includes first brightness information, second brightness information, and optionally one or more optional brightness information collected in other different transmission directions; S22: Calculating polarization characteristic parameters of an area within the camera field of view where brightness changes as the transmission direction of the linear polarizer changes; S23: comparing the polarization characteristic parameter calculated from the brightness change region with a typical polarization characteristic parameter range in a preset reference model to generate a comparison result; S24: Identifying the source of the brightness change based on the comparison result, and distinguishing between a portion dominated by the light reflected from the surface of the transparent medium and a portion dominated by a light source or object in the target scene that has its own polarization characteristics; S25: excluding or compensating for the brightness change portion dominated by the light source or object having its own polarization characteristics in the target scene to determine the contribution of the light reflected from the surface of the transparent medium to the total brightness; Step S25 includes: S251: monitoring the temporal variation of the polarization characteristic parameter of the brightness variation portion during each brightness information collected under different transmission directions to obtain temporal variation of the polarization characteristic parameter; S252: When the amplitude of the polarization parameter change exceeds a preset threshold, adjusting, based on the temporal change of the obtained polarization characteristic parameter, a strategy or parameters used for excluding or compensating for the brightness change portion dominated by the identified light source or object having polarization characteristics in the target scene, to obtain an adjusted exclusion or compensation strategy or parameters; S253: Apply the adjusted exclusion or compensation processing strategy or parameters to exclude or compensate for the brightness change portion dominated by the light source or object with polarization characteristics in the target scene, and calculate the contribution of the reflected light on the surface of the transparent medium to the total brightness.

2. The method for detecting visible light brightness of a camera according to claim 1, wherein: Step S22 includes: S221: The first brightness information and the second brightness information in step S21, as well as one or more optional brightness information collected in other different transmission directions, are collectively referred to as multi-frame polarization brightness information; S222: Determine a spatial offset of a corresponding scene area in each frame of brightness information caused by a relative displacement or posture change between the camera and the target scene during acquisition of the multiple frames of polarization brightness information; S223: Performing image registration processing on the multiple frames of polarization brightness information according to the determined spatial offset to generate a set of spatially aligned multiple frames of polarization brightness information, ensuring that each brightness value used to calculate the polarization characteristics of the same scene point in the spatially aligned multiple frames of polarization brightness information corresponds to the same physical area of ​​the target scene; S224: Based on the spatially aligned multi-frame polarization brightness information, calculate polarization characteristic parameters of an area in the camera field of view where brightness changes along the transmission direction of the linear polarizer.

3. The method for detecting visible light brightness of a camera according to claim 2, wherein: The polarization characteristic parameters include one or a combination of two of the polarization degree and the polarization main axis direction calculated according to the corresponding brightness information.

4. The method for detecting visible light brightness of a camera according to claim 2, wherein: Step S222 includes: S2221: Applying an image structure extraction algorithm to each frame of the multiple frames of polarization brightness information to generate a structural feature map corresponding to the frame of image; S2222: Select one frame from the multiple frames of polarization brightness information as a reference frame, and use a structural feature map corresponding to the reference frame image as a reference structural feature map; S2223: Determine an initial region correspondence relationship between the reference structure feature map and structure feature maps corresponding to other frame images except the reference frame by performing a region-based cross-correlation operation or a phase correlation operation; S2224: Perform consistency check on the determined initial region correspondence, and determine the spatial offset of each frame relative to the reference frame based on the region correspondence that meets the consistency condition.

5. The method for detecting visible light brightness of a camera according to claim 4, wherein: The structural feature map includes edge information or gradient direction information of the image to reduce the impact of scene illumination changes independent of polarizer rotation on pixel intensity in the multi-frame polarization brightness information.

6. The method for detecting visible light brightness of a camera according to claim 4, wherein: Step S2224 includes: S22241: Extract and match two or more sets of feature point coordinates from multiple frames of polarized brightness images, directly fit the affine transformation matrix using the least squares method, filter out matching points with excessive errors in the initial transformation based on a preset residual threshold, and re-perform the least squares fit on the remaining matching points to obtain the final geometric transformation model; S22242: For each of the initial region correspondences, calculating the degree of conformity between the correspondence and the geometric transformation model; S22243: Determine which region correspondences in the initial region correspondences satisfy the consistency condition based on the calculated degree of conformity.

7. The method for detecting visible light brightness of a camera according to claim 1, wherein: Step S3 includes: S31: performing a first correction process on at least one of the first brightness information and the second brightness information, or a combination thereof, based on a contribution of the light reflected from the surface of the transparent medium to the total brightness, to obtain intermediate brightness information in which the influence of the light reflected from the surface of the transparent medium has been reduced; S32: Obtaining spectral transmission characteristics or color characteristic parameters of the transparent medium; S33: Based on the acquired spectral transmission characteristics or color characteristic parameters, a second correction process is performed on the intermediate brightness information, wherein the second correction process is used to compensate for the spectral change or intensity attenuation caused by the transparent medium to the transmitted light of the target scene, so as to obtain a target brightness representing the target scene on the other side of the transparent medium.

8. A visible light brightness detection system for a camera, characterized in that: The system comprises: Polarization information acquisition module: acquires first brightness information of the scene in the camera's field of view when the linear polarizer is in a first transmission direction when the camera photographs the target scene through a transparent medium, and obtains second brightness information of the scene in the camera's field of view when the linear polarizer is in a direction different from the first transmission direction; a characteristic analysis and identification module for analyzing, based on the first brightness information and the second brightness information, characteristics of brightness changes as the transmission direction of the linear polarizer changes, so as to distinguish between the portion of light reflected by the surface of the transparent medium and the portion of light transmitted by the target scene, and thereby determine the contribution of the light reflected by the surface of the transparent medium to the total brightness; a brightness correction module configured to correct at least one of the first brightness information and the second brightness information, or a combination thereof, based on a contribution of the reflected light on the surface of the transparent medium to the total brightness, so as to obtain a target brightness representing the target scene on the other side of the transparent medium; The characteristic analysis and identification module is further used to: obtain each brightness information collected under different transmission vibration directions, each brightness information including first brightness information, second brightness information and optionally one or more optional brightness information collected under other different transmission vibration directions; Calculating polarization characteristic parameters of an area within the camera field of view where brightness changes as the transmission direction of the linear polarizer changes; Comparing the polarization characteristic parameter calculated from the brightness change region with a typical polarization characteristic parameter range in a preset reference model to generate a comparison result; Based on the comparison results, identifying the source of the brightness change, distinguishing between a portion dominated by light reflected from the surface of the transparent medium and a portion dominated by a light source or object in the target scene that has its own polarization characteristics; Eliminate or compensate for the brightness variation dominated by the light source or object with its own polarization characteristics in the target scene to determine the contribution of the light reflected from the surface of the transparent medium to the total brightness; The excluding or compensating for the brightness change portion dominated by the light source or object having polarization characteristics in the target scene to determine the contribution of the reflected light on the surface of the transparent medium to the total brightness also includes: Monitoring the temporal variation of the polarization characteristic parameter of the brightness variation portion during each brightness information collected under different transmission directions to obtain temporal variation of the polarization characteristic parameter; When the amplitude of the polarization parameter change exceeds a preset threshold, adjusting, based on the temporal change of the obtained polarization characteristic parameters, the strategy or parameters used for excluding or compensating the brightness change portion dominated by the identified light source or object having polarization characteristics in the target scene, to obtain an adjusted exclusion or compensation strategy or parameters; Applying the adjusted exclusion or compensation processing strategy or parameters, the brightness change portion dominated by the light source or object with its own polarization characteristics in the target scene is excluded or compensated, and the contribution of the reflected light on the surface of the transparent medium to the total brightness is calculated.

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