Projector brightness adjustment method

Abstract

The present application relates to the technical field of projectors, and particularly relates to a method for adjusting the brightness of a projector, including: obtaining in real time the reflectivity distribution data of the surface of the projection area and calculating the local reflectivity gradient; non-uniformly partitioning the projection area according to the magnitude of the local reflectivity gradient; for each partition, calculating the compensation brightness based on the reflectivity distribution data and the target brightness; driving the projection light source to output according to the compensation brightness, and updating the reflectivity distribution data in real time. The present application has the effect of solving the problem of uneven brightness and darkness of the picture caused by changes in reflectivity.

Description

Technical Field

[0001] This application relates to the technical field of projectors, and particularly relates to a method for adjusting the brightness of a projector. Background Art

[0002] The popularization and innovation of projection technology are continuously expanding its application scenarios, extending from traditional meeting rooms and classrooms to home theaters, outdoor displays, and even the mobile business field. Users' requirements for projection image quality are not limited to resolution and color performance, but also focus on brightness consistency, energy efficiency, and dynamic adaptability in complex environments. Although existing automatic brightness adjustment technologies have made progress in ambient light perception and content analysis, their core frameworks still have significant limitations, especially in the adaptability to non-ideal projection surfaces, which has long faced technical bottlenecks and restricted the further improvement of the user experience.

[0003] Mainstream brightness adjustment schemes mainly rely on two technical paths: ambient light sensing and image content analysis. Ambient light feedback control uses a photoelectric sensor to collect the ambient light intensity in real time and adjusts the light source output power through a closed-loop algorithm. These methods default that the ambient light is evenly distributed and the projection surface is an ideal diffuse reflector, but in fact, they cannot perceive the spatial differences in the surface reflection characteristics. For example, a dark wall will significantly attenuate the reflected light intensity, causing the sensor to misjudge that the ambient light is sufficient and reduce the brightness, while the actual image is dim and blurry due to insufficient reflectivity. More seriously, the sensor is easily interfered by strong light sources outside the projection area, and the measurement deviation is particularly significant on mirror or semi-transparent surfaces (such as glass), resulting in compensation failure.

[0004] Image content adaptive adjustment dynamically adjusts the output parameters by analyzing the brightness histogram of the video signal, attempting to enhance details in dark scenes or suppress overexposure in bright scenes. However, these methods only process the original signal and do not incorporate the impact of surface reflectivity on the final display effect into the calculation model. When the same high-brightness image is projected onto a white wall and a gray wall, the actual visual perception difference can reach more than 30%, but traditional algorithms are powerless in this regard. Even more, the strategy of globally increasing the brightness to compensate for low-reflection surfaces often leads to overexposure in high-reflection areas, resulting in the loss of high-light details and the compression of the dynamic range.

[0005] Although preset modes and manual calibration functions can be used as supplementary solutions, allowing users to select fixed scene modes or optimize parameters through a colorimeter. These methods can improve the experience in a static environment, but it is difficult to cope with the dynamic changes in surface reflectivity. In emerging scenarios such as smart dimming glass and mobile projection screens, the reflectivity distribution may change several times per second, and the static calibration parameters quickly become invalid. Facing frequent manual adjustments, ordinary users not only experience fragmentation but also have difficulty achieving precise optimization due to lack of professional knowledge.

[0006] Projection display is essentially a three-element system of light-surface-human eye. The surface reflectivity is a key intermediary variable that directly determines the final image quality. The theoretical assumption of an ideal diffuse reflector frequently fails in practical applications: the concave-convex structure of textured wallpaper leads to a disordered distribution of incident angles, the selective reflection of warm-colored paint on specific wavelengths of light causes color deviation, and the glare area produced by mirror materials destroys the uniformity of the picture. The addition of dynamic surface characteristics further increases the complexity: the reflectivity of smart glass can change instantaneously with electrical signals, and the projection area on the surface of the rotating booth continuously shifts. The response delay of the traditional technical framework to such scenes can reach hundreds of milliseconds, resulting in flicker and smear visible to the naked eye.

[0007] The coupling effect of ambient light and surface reflection is often underestimated. When the ambient light intensity is close to that of the projected light, a slight change in reflectivity will significantly change the contrast of the picture. Taking gray walls and white walls as examples, the former has a low reflectivity, which makes the projected light dominate, while the latter has a high reflectivity, which increases the reflection of ambient light, making dark scenes white and reducing color saturation. The existing algorithm does not establish a dynamic model of ambient light, projected light, and surface reflection. It only adjusts the output through simple addition and subtraction operations, which makes it difficult to achieve physically accurate brightness compensation.

[0008] In recent years, academia and industry have tried to introduce surface reflectivity compensation, but mature solutions are still to be developed. Methods based on pre-stored surface databases rely on users to manually input material types and cannot adapt to local differences on the same surface; camera-assisted measurement solutions are severely affected by ambient light and require too much computing power for real-time processing; dual-light source detection technology requires dedicated hardware support, and cost and power consumption restrict commercialization. These attempts have not solved the core problem due to insufficient accuracy or poor real-time performance.

[0009] The evolution of market demand is driving a paradigm shift in technology. The popularity of IoT devices and the emergence of smart materials are making projection scenes increasingly complex and diverse. Users are in urgent need of a solution to the above problems to break through the path dependence of traditional ambient light and content analysis. Summary of the invention

[0010] In order to solve the above problems, the present application provides a method for adjusting the brightness of a projector.

[0011] The present application provides a method for adjusting the brightness of a projector, which adopts the following technical solution:

[0012] A method for adjusting the brightness of a projector comprises the following steps:

[0013] Obtain the reflectivity distribution data of the projection area surface in real time and calculate the local reflectivity gradient;

[0014] The projection area is non-uniformly partitioned according to the magnitude of the local reflectivity gradient;

[0015] For each partition, calculate the compensation luminance based on the reflectance distribution data and the target luminance;

[0016] Drive the projection light source to output according to the compensation luminance, and update the reflectance distribution data in real time.

[0017] In one embodiment: The step of obtaining the reflectance distribution data on the surface of the projection area in real time and calculating the local reflectance gradient specifically includes:

[0018] Based on the acquisition position of the projection area, obtain the reflected light intensity, the test light intensity, and the surface normal inclination angle. The calculation formula for the reflectance distribution data at the position (x, y) is:

[0019] ;

[0020] Wherein, is the reflected light intensity, is the test light intensity, is the surface normal inclination angle, and k is the sensor calibration coefficient;

[0021] The calculation formula for the local reflectance gradient at the position (x, y) is:

[0022] ;

[0023] In the formula, and are obtained by calculating the partial derivatives using the central difference method for the discretized reflectance matrix ρ[i][j]. The formula is:

[0024] ;

[0025] ;

[0026] Wherein, Δx and Δy are the sensor pixel pitches.

[0027] In one embodiment: The step of non-uniformly partitioning the projection area according to the magnitude of the local reflectance gradient specifically includes:

[0028] Divide the projection area into initial large partitions according to a preset specification;

[0029] Compare the local reflectance gradient of the initial large partition with a preset gradient threshold. If it is greater than the gradient threshold, split the initial large partition into multiple sub-partitions, and recalculate the local reflectance gradient of each sub-partition;

[0030] After each split, the local reflectance gradients of the sub-regions are compared again with a preset gradient threshold until all regions pass the determination; where passing the determination means that the local reflectance gradient is less than the gradient threshold, or the size of the sub-region reaches the minimum preset size.

[0031] In one embodiment: the step of non-uniformly partitioning the projection area according to the magnitude of the local reflectance gradient further includes:

[0032] Traverse all regions and detect whether adjacent regions meet the merging conditions; where the merging conditions are that the local reflectance gradients are both less than or equal to half of the gradient threshold and the difference in the average reflectance is less than a preset difference;

[0033] Merge the adjacent regions that meet the conditions into super-pixel regions;

[0034] Perform a morphological erosion operation on the boundary of the merged region to eliminate the jagged edges.

[0035] In one embodiment: the calculation formula for compensating the brightness is:

[0036] ;

[0037] In the formula, is the target brightness, is the local reflectance, is the global average reflectance, is the contrast adaptive weight;

[0038] Among them, the local reflectance refers to the average reflectance of the region.

[0039] In one embodiment: when the surface of the region is inclined, the calculation formula for the local reflectance is:

[0040] ;

[0041] In the formula, is the physical area of the i-th region;

[0042] When the surface of the region is not inclined, the calculation formula for the local reflectance is:

[0043] ;

[0044] In the formula, is the area of the region.

[0045] In one embodiment: the adjustment method for the contrast adaptive weight is:

[0046] When the dynamic range of the image content is greater than a preset value, the calculation formula for the contrast adaptive weight is:

[0047] ;

[0048] In the formula, is the dynamic range;

[0049] When a rapid screen switch is detected, the contrast adaptive weight decays exponentially, and its calculation formula is:

[0050] ;

[0051] In the formula, τ is the decay time constant;

[0052] Among them, the calculation formula of the dynamic range is:

[0053] ;

[0054] In the formula, is the highest brightness value of all partitions in the entire projection area, is the lowest brightness value of all partitions in the entire projection area.

[0055] In one embodiment: The step of detecting a rapid screen switch is: If the frame difference method detects a rapid switch, and at least one of the optical flow velocity or scene cut detects a rapid switch.

[0056] In one embodiment: It further includes an exception handling step:

[0057] If the local reflectivity is less than the preset reflectivity threshold, it is determined as an uncompensable area, marked as a shadow area and the brightness of this partition is reduced.

[0058] In one embodiment: The brightness of the partition marked as the shadow area is adjusted to 0.3 times the target brightness. Description of the Drawings

[0059] Figure 1 is a schematic diagram of the steps of the projector brightness adjustment method in this embodiment. Detailed Description of the Embodiment

[0060] The following further describes the present application in detail with reference to the drawings.

[0061] A projector brightness adjustment method, as Figure 1 shown, includes the following steps:

[0062] S200. Obtain the reflectivity distribution data of the surface of the projection area in real time and calculate the local reflectivity gradient.

[0063] Among them, the reflectance distribution data is obtained by a multi-modal sensor. The multi-modal sensor includes a visible light camera, a time-of-flight (ToF) sensor, and an active light source array. The visible light camera captures the color distribution (such as whether the wall surface is warm-toned) and texture features (such as wood grain, tile joints) of the projection surface through the RGB channels, analyzes the brightness distribution after the projection light is reflected, and generates a reflected light intensity map. The time-of-flight (ToF) sensor measures the distance d(x,y) of each point on the projection surface, generates a depth map, and calculates the surface normal direction θ(x,y) through the depth difference between adjacent points. The active light source array emits test light spots with known intensities, and the measured reflected light intensity is obtained through measurement by the visible light camera.

[0064] This step specifically includes:

[0065] Based on the acquisition position of the projection area, the reflected light intensity, the test light intensity, and the surface normal inclination angle are obtained. The coordinates of the acquisition position are represented by (x,y). Among them, the calculation formula for the reflectance distribution data located at the position (x,y) is:

[0066] ;

[0067] Among them, is the reflected light intensity, is the test light intensity, is the surface normal inclination angle, and k is the sensor calibration coefficient. represents the reflectance at any position (x,y) on the projection surface. It is a continuous function with a value range of [0,1], where 0 represents full absorption and 1 represents full reflection.

[0068] The local reflectance gradient located at the position (x,y) represents the maximum change rate of the reflectance at the position (x,y) on the projection surface, with the unit of reflectance unit / distance unit (such as % / mm). The larger the magnitude of the gradient, the more significant the difference in reflectance between adjacent regions (such as black spots on a white wall, specular reflection points, wall surface unevenness, cracks, or edges of decorations, etc.). Its calculation formula is:

[0069] ;

[0070] In the formula, and are obtained by calculating the partial derivatives of the discretized reflectance matrix ρ[i][j] using the central difference method. The formula is:

[0071] ;

[0072] ;

[0073] Among them, Δx and Δy are the sensor pixel pitches.

[0074] S400. Non-uniformly partition the projection area according to the magnitude of the local reflectivity gradient.

[0075] Specifically, partition the projection area through the local reflectivity gradient, and by means of segmentation and merging, increase the low-gradient area and reduce the high-gradient area. Among them, the high-gradient area is determined as the area with sudden reflectivity changes (such as wall cracks, material junctions). By reducing the high-gradient area, the adjustment accuracy is improved to achieve millimeter-level compensation, increasing the low-gradient area reduces the light source output frequency, reduces the calculation load, and saves power consumption.

[0076] This step specifically includes:

[0077] Divide the projection area into initial large partitions according to a preset specification. The initial large partitions are set according to the area of the projection area. Usually, in order to reduce the calculation load, it is set to 50mm×50mm.

[0078] Compare the local reflectivity gradient of the initial large partition with a preset gradient threshold. If it is greater than the gradient threshold, split the initial large partition into multiple sub-partitions and recalculate the local reflectivity gradient of each sub-partition. Among them, the number of sub-partitions formed after each split is n 2 , where n is a natural number.

[0079] After each split, re-compare the local reflectivity gradient of each sub-partition with the preset gradient threshold until all partitions pass the determination. Among them, passing the determination means that the local reflectivity gradient is less than the gradient threshold, or the size of the sub-partition reaches the minimum preset size. The purpose of setting the minimum preset size is to control the calculation load, usually set to 2mm*2mm.

[0080] After all partitions pass the determination, traverse all partitions to detect whether adjacent partitions meet the merging conditions. Among them, the merging conditions are that the local reflectivity gradients are all less than or equal to half of the gradient threshold and the difference in reflectivity means is less than a preset difference.

[0081] Merge the adjacent partitions that meet the conditions into superpixel partitions. The size of the superpixel partitions is usually not larger than the initial large partition. However, when the processor load exceeds 80%, emergency merging can be performed, and the superpixel partitions formed by forcibly merging the low-gradient areas can be larger than the initial large partition.

[0082] Perform a morphological erosion operation on the boundaries of the merged partitions to eliminate jagged edges.

[0083] S600. For each partition, calculate the compensation brightness based on the reflectivity distribution data and the target brightness.

[0084] The calculation formula for the compensation brightness is:

[0085] ;

[0086] In the formula, is the target brightness, is the local reflectivity, is the global average reflectivity, is the contrast adaptive weight.

[0087] Among them, the local reflectivity refers to the average reflectivity of the partition. Through dynamic partition division, the continuous reflectivity field is discretized into a finite number of local values , and each represents the reflection characteristics of the corresponding partition.

[0088] The local reflectivity can be obtained by calculating the following two formulas. In this implementation, according to the different surface conditions of the partitions, the following two formulas are used for calculation respectively.

[0089] When there is an inclination on the partition surface, that is, the actual surface includes scenarios such as inclination, concavity, and convexity, the accuracy of the local reflectivity depends on the surface normal inclination angle . Therefore, the local reflectivity is cosine-corrected and weighted according to the surface normal inclination angle provided by the ToF sensor for , and its calculation formula is:

[0090] ;

[0091] In the formula, is the physical area of the i-th partition.

[0092] When there is no inclination on the partition surface, that is, the partition is located on an ideal flat surface, the calculation formula of the local reflectivity is:

[0093] ;

[0094] In the formula, is the partition area (unit: mm2), represents the physical distance of the partition surface in the x / y two directions.

[0095] Among them, through the above dynamic partitioning, the in the high-gradient region is closer to the true local value and adjacent region interference is suppressed. In addition, it should be noted that using different calculation formulas according to whether there is an inclination on the partition surface is mainly to reduce the calculation load while ensuring the calculation accuracy. If the processor load is sufficient, only the calculation formula after cosine correction and weighting can also be used. Conversely, only the second calculation formula can also be used.

[0096] In this embodiment, the adjustment method of the contrast adaptive weight is:

[0097] When the dynamic range of the image content is greater than the preset value, the calculation formula for the contrast adaptive weight is:

[0098] ;

[0099] In the formula, is the dynamic range. Among them, the calculation formula for the dynamic range is:

[0100] ;

[0101] In the formula, is the highest brightness value of all partitions in the entire projection area, is the lowest brightness value of all partitions in the entire projection area.

[0102] When a rapid screen switch is detected, the contrast adaptive weight decays exponentially, and its calculation formula is:

[0103] ;

[0104] In the formula, τ is the decay time constant.

[0105] Among them, the steps to detect a rapid screen switch are: if the frame difference method detects a rapid switch, and at least one of the optical flow velocity or scene cut detects a rapid switch. Through the above multi-modal decision logic method, the compensation weight is reduced during rapid switching to avoid brightness flicker caused by delayed reflectivity update.

[0106] The technical standard for detecting a rapid screen switch is that the content difference between adjacent frames exceeds the threshold, usually manifested as:

[0107] 1. The brightness histogram changes violently (such as the overall brightness suddenly changes by more than 50%);

[0108] 2. The motion vector suddenly increases (such as the optical flow velocity exceeds 30 pixels / frame);

[0109] 3. Scene cut detection (such as the edge feature matching degree drops by more than 70%).

[0110] The frame difference method detects the sudden change of the overall brightness, and its specific steps include:

[0111] Brightness channel extraction: Convert the input video frame into a grayscale image .

[0112] Difference calculation: Calculate the difference between adjacent frames .

[0113] Normalization processing: , where is the resolution.

[0114] Threshold determination: If > τ, it is determined as a fast switch.

[0115] The specific steps of optical flow motion analysis include:

[0116] Sparse optical flow calculation: Use the Lucas-Kanade algorithm to track the motion speed of feature points .

[0117] Average speed calculation, and the calculation formula is:

[0118] ;

[0119] Motion surge determination: If , it is confirmed as a fast switch, where is a preset value, such as 20 pixels / frame, etc.

[0120] The steps of scene cutting detection specifically include:

[0121] Edge feature extraction: Use the Canny operator to detect the edge map E of the current frame t .

[0122] Feature matching degree calculation, and the calculation formula is:

[0123] ;

[0124] In the formula, represents the number of edge pixels that coexist in two frames, and its calculation method is pixel-by-pixel comparison. If both positions in the two frames are 1, the result is 1, otherwise it is 0; represents the sum of all edge pixels in two frames, and its calculation method is pixel-by-pixel comparison. If at least one of the same positions in the two frames is 1, the result is 1, otherwise it is 0.

[0125] Scene cutting determination: If < m, it is determined as a scene switch, where the value of m is less than 1.

[0126] In addition, in one of the embodiments, an exception handling step is further included, and this step specifically includes:

[0127] If the local reflectivity is less than the preset reflectivity threshold, it is determined as an uncompensable area, marked as a shadow area and the brightness of this partition is reduced.

[0128] Among them, the brightness of the partition marked as the shadow area is adjusted to 0.3 times of the target brightness.

[0129] S800. Drive the projection light source to output according to the compensated brightness, and update the reflectivity distribution data in real time.

[0130] The embodiments of this specific implementation manner are all preferred embodiments of this application, and do not limit the protection scope of this application. Therefore, all equivalent changes made according to the structure, shape, and principle of this application shall be covered within the protection scope of this application.

Claims

1. A method for adjusting the brightness of a projector, characterized in that, It includes the following steps: Obtain the reflectance distribution data on the surface of the projection area in real time, and calculate the local reflectance gradient; Perform non-uniform partitioning on the projection area according to the magnitude of the local reflectance gradient; For each partition, calculate the compensation brightness based on the reflectance distribution data and the target brightness; Drive the projection light source to output according to the compensation brightness, and update the reflectance distribution data in real time; Among them, the step of performing non-uniform partitioning on the projection area according to the magnitude of the local reflectance gradient specifically includes: Divide the projection area into initial large partitions according to a preset specification; Compare the local reflectance gradient of the initial large partition with a preset gradient threshold. If it is greater than the gradient threshold, split the initial large partition into multiple sub-partitions, and recalculate the local reflectance gradient of each sub-partition; After each split, re-compare the local reflectance gradient of each sub-partition with the preset gradient threshold until all partitions pass the determination; where passing the determination means that the local reflectance gradient is less than the gradient threshold, or the size of the sub-partition reaches the minimum preset size.

2. The projector brightness adjustment method according to claim 1, wherein: The step of obtaining the reflectance distribution data on the surface of the projection area in real time and calculating the local reflectance gradient specifically includes: Based on the acquisition position of the projection area, obtain the reflected light intensity, the test light intensity, and the surface normal inclination angle. The calculation formula for the reflectance distribution data at the position (x, y) is: ； wherein, is the reflected light intensity, is the test light intensity, is the surface normal inclination angle, and k is the sensor calibration coefficient; The calculation formula for the local reflectance gradient at the position (x, y) is: ； In the formula, and are obtained by calculating the partial derivatives of the discretized reflectance matrix ρ[i][j] using the central difference method, and the formula is: ； ； Among them, Δx and Δy are the sensor pixel pitches.

3. The projector brightness adjustment method according to claim 1, wherein: The step of performing non-uniform partitioning on the projection area according to the magnitude of the local reflectance gradient further includes: Traverse all partitions and detect whether adjacent partitions meet the merging conditions; where the merging conditions are that the local reflectance gradients are all less than or equal to half of the gradient threshold and the difference in the average reflectance is less than a preset difference; Merge the adjacent partitions that meet the conditions into super-pixel partitions; Perform a morphological erosion operation on the boundary of the merged partition to eliminate the jagged edges.

4. The projector brightness adjustment method according to claim 1, characterized in that: The calculation formula for the compensation brightness is: ； Wherein, is the target brightness, is the local reflectivity, is the global average reflectivity, is the contrast adaptive weight; Among them, the local reflectance refers to the average reflectance of the partition.

5. The projector brightness adjustment method according to claim 4, characterized in that: The calculation formula for the local reflectance is: ； In the formula, is the physical area of the i-th partition; Or / and, the calculation formula for the local reflectance is: ； In the formula, is the area of the partition.

6. The projector brightness adjustment method according to claim 4, wherein: The adjustment method for the contrast adaptive weight is: When the dynamic range of the image content is greater than a preset value, the calculation formula for the contrast adaptive weight is: ； In the formula, is the dynamic range; When it is detected that the screen is switched quickly, the contrast adaptive weight decays exponentially, and its calculation formula is: ； In the formula, τ is the decay time constant; Among them, the calculation formula for the dynamic range is: ； Wherein, is the highest luminance value of all partitions within the entire projection area, is the lowest luminance value of all partitions within the entire projection area.

7. The projector brightness adjustment method according to claim 6, wherein: The step of detecting that the screen is switched quickly is: if the frame difference method detects a quick switch, and at least one of the optical flow velocity or the scene cut detects a quick switch.

8. The projector brightness adjustment method according to claim 4, wherein: It further includes an exception handling step: If the local reflectance is less than a preset reflectance threshold, it is determined as an uncompensable area, marked as a shadow area, and the brightness of this partition is reduced.

9. The projector brightness adjustment method according to claim 8, wherein: The brightness of the partition marked as the shadow area is adjusted to 0.3 times the target brightness.

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