Projector and optical parameter adjusting method and system

Abstract

The invention discloses a projector and an optical parameter adjusting method and system, and the method comprises the steps: collecting the ambient light intensity and ambient light color temperature, and analyzing an input video signal; the LCD voltage control quantity is controlled based on the ambient light intensity, the target projection brightness, the ambient light color temperature and the image main color temperature difference value, rapid brightness response is achieved, and long-term color cast is effectively eliminated. The LED current control quantity is controlled based on the brightness histogram and the main color gamut saturation of the input video signal, the backlight requirement can be pre-judged, and the color boundary contrast is effectively enhanced. According to the invention, based on the ambient light data and the input video signal, the LCD voltage control quantity and the LED current control quantity are obtained through analysis and calculation, so that LCD display and LED backlight parameter adjustment control of the display device are realized, collaborative optimization of ambient light and image content is realized, color gamut loss and gray-scale fault are effectively reduced, and the display quality is improved. Different scene environments and display contents can be effectively adapted, and the picture display effect is improved.

Description

Technical Field

[0001] This invention belongs to the technical field of intelligent optical parameter adjustment methods for projectors, specifically relating to a projector and an optical parameter adjustment method and system. Background Technology

[0002] An LCD projector is a display device that uses liquid crystal display technology to adjust transmittance and reflectance by controlling the arrangement of liquid crystal molecules, thereby generating images and projecting them through an optical system. It mainly consists of a light source, a liquid crystal panel, driving circuitry, and a complex optical system. LCD projectors have good color performance and high light utilization efficiency, making them widely used in home theaters, business presentations, and educational settings. However, ambient lighting conditions vary significantly in different scenarios, and high dynamic range video content places higher demands on the adaptive adjustment capabilities of LCD projectors' optical parameters, requiring simultaneous optimization of multiple optical parameters. To ensure the display effect of different content in different scenarios, typical LCD projectors require manual adjustment of optical parameters. However, professional tuning of optical parameters relies on experienced technicians, limiting the ease of use and image quality consistency of the projector.

[0003] Therefore, existing technologies utilize adaptive optical parameter adjustment methods for LCD projectors to automatically adjust optical parameters for different display content in different scenarios, ensuring display quality. Current adaptive optical parameter adjustment methods use ambient light sensors to collect ambient brightness and adjust screen brightness accordingly. While this method quickly adapts to ambient light, it neglects the matching relationship between color temperature and image content, leading to a loss of color saturation in daylight scenarios. Existing adaptive optical parameter adjustment methods typically adjust the contrast of the displayed image using the image brightness histogram, effectively optimizing visual experience. However, they do not consider the impact of high-frequency details on the gamma curve, resulting in the loss of detail in dark areas. Therefore, while existing adaptive optical parameter adjustment methods can quickly adapt to different environments and display scenarios, improving visual experience, the adjustment method is relatively simple, resulting in poor image quality. Summary of the Invention

[0004] The technical problem to be solved by the present invention is to overcome the defect of poor image display effect of the optical parameter adaptive adjustment method of the projector in the prior art, thereby providing a projector and an optical parameter adjustment method and system.

[0005] An optical parameter adjustment method includes the following steps: Collect ambient light data, including ambient light intensity and ambient light color temperature; Acquire the input video signal, analyze the input video signal, and generate a luminance histogram, dynamic contrast threshold, and main color gamut saturation. The target projection brightness is calculated based on the mapping relationship between the ambient light intensity and the preset human eye comfort model; Based on the ambient light color temperature and the main color gamut saturation, calculate the adaptive white balance compensation matrix; Based on the ambient light data and the input video signal, control instructions are calculated, including LCD voltage control quantities and LED current control quantities; The LCD voltage control adopts a proportional-integral control strategy, where the proportional term is the ratio of the difference between the ambient light intensity and the target projection brightness, and the integral term is the integral term of the difference between the ambient light color temperature and the image main color temperature. The LED current control adopts a differential-second-order differential control strategy. The differential term is the differential term of the entropy value of the brightness histogram, and the second-order differential term is the second-order differential term of the main color gamut saturation gradient magnitude. The control commands are used to control the LCD, backlight LED, and color wheel of the display device.

[0006] Furthermore, when the ambient light intensity is within a preset range and the average saturation of the input video signal is less than a preset threshold, the ambient light data, the features of the input video signal, and the user's operation preferences are input into a multi-mode adaptive learning engine. The multi-mode adaptive engine is a long short-term memory network, which obtains the backlight gain coefficient and color temperature offset. The display screen is adjusted based on the backlight gain coefficient and the color temperature offset.

[0007] Furthermore, the multi-mode adaptive engine is a three-layer convolutional long short-term memory network. The input layer includes ambient light data, features of the input video signal, and user operation preferences. The convolutional layer extracts features through three sets of parallel one-dimensional convolutional kernels. The LSTM layer models temporal dependencies through a bidirectional long short-term memory network. The output layer generates backlight gain coefficients and color temperature offsets through activation functions.

[0008] Furthermore, the ratio term is the product of the ratio coefficient and the difference between the ambient light intensity and the target projection brightness. When the dynamic contrast exceeds a preset threshold, the ratio term increases by a preset percentage. The integral term is the product of the integral coefficient and the integral of the difference between the ambient light color temperature and the image main color temperature. When the red channel in the main color gamut saturation feature exceeds a preset threshold, the integral term is reduced by a preset ratio, activating the red filter dwell time compensation of the color wheel.

[0009] Furthermore, the differential term is the product of the differential coefficient and the differential of the luminance histogram entropy value. When the rate of change of ambient light intensity is greater than a preset threshold, the differential term increases by a preset ratio, and the backlight pulse pre-emphasis mode is enabled. The second-order derivative term is the product of the second-order derivative coefficient and the second-order derivative of the main color gamut saturation gradient magnitude. When the dynamic contrast exceeds a preset threshold, the second-order derivative term is reduced by a preset percentage.

[0010] Furthermore, the LED pulse width modulation control quantity is expressed as: ; in, This represents the current-to-duty cycle conversion factor. This represents the flicker suppression gain coefficient. This represents an evaluation index based on a human eye flicker sensitivity model; when the rate of change of ambient light intensity exceeds a preset threshold, the flicker suppression gain coefficient increases, activating PWM leading-edge spike overshoot.

[0011] Furthermore, the control commands include color wheel control commands, which include color wheel phase control quantities and color wheel angular velocity compensation control quantities. The color wheel phase control value is expressed as: ; The color wheel angular velocity control value is expressed as: ; in, This indicates the deviation between the actual phase of the color wheel and the frame synchronization signal. and These are phase control parameters. Indicates the moment of inertia of the color wheel. This represents the damping coefficient.

[0012] Furthermore, the control command includes a filter control command, which includes a filter dwell time control amount, expressed as: ; in, Indicates the baseline dwell time. Indicates compensation gain. Indicates the percentage of pixels in the main color gamut. This represents the total number of pixels in the image.

[0013] An optical parameter adjustment system for adjusting optical parameters using the aforementioned optical parameter adjustment method, characterized in that it comprises: Ambient light sensor, used to collect ambient light intensity and color temperature data; The image analysis module is used to parse the input video signal and extract the image brightness histogram, dynamic contrast threshold, and main color gamut saturation features. The processor module is used to calculate the target projection brightness based on the mapping relationship between ambient light intensity and a preset human eye comfort model, generate adaptive white balance compensation parameters by combining ambient light color temperature and image main color gamut features, and optimize the gamma curve segment adjustment strategy according to the proportion of high-frequency details in the image. The optical actuator is used to adjust the deflection voltage of liquid crystal molecules through a three-channel synchronous driving mechanism according to the control instructions of the processor module, thereby changing the light transmittance, dynamically modulating the pulse width and current intensity of the backlight LED, and controlling the rotation phase angle and angular acceleration of the color wheel.

[0014] A projector that achieves optical parameter adjustment using the aforementioned optical parameter adjustment method.

[0015] Beneficial Effects: This invention discloses a projector and an optical parameter adjustment method and system. It collects ambient light intensity and ambient light color temperature while simultaneously analyzing the input video signal. The LCD voltage is controlled by a proportional term based on the difference between ambient light intensity and target projection brightness, achieving rapid brightness response. The LCD voltage is controlled by an integral term based on the difference between ambient light color temperature and the image's primary color temperature, effectively eliminating long-term color shift. The LED current is controlled by a differential term based on the entropy value of the brightness histogram of the input video signal, predicting backlight requirements. The LED current is controlled by a second-order differential term based on the magnitude of the primary color gamut saturation gradient, effectively enhancing color boundary contrast. This invention analyzes and calculates LCD voltage and LED current based on ambient light data and input video signals, thereby achieving parameter adjustment and control of the LCD display and LED backlight of the display device. It realizes coordinated optimization of ambient light and image content, effectively reducing color gamut loss and grayscale banding, effectively adapting to different scene environments and display content, and improving the image display effect. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0017] Figure 1 This is a flowchart of the main method of the present invention. Detailed Implementation

[0018] To make the above-mentioned objectives, features, and advantages of this application more apparent and understandable, the specific embodiments of this application are described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of this application. However, this application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of this application. Therefore, this application is not limited to the specific embodiments disclosed below.

[0019] In the description of this application, it should be understood that features specified as "first" or "second" may explicitly or implicitly include at least one of those features. In the description of this application, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified.

[0020] In this application, unless otherwise expressly specified and limited, the terms "installation," "connection," "joining," and "fixing," etc., should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral part; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; they can refer to the internal communication of two components or the interaction between two components, unless otherwise expressly limited. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0021] Example 1: Reference Figure 1 As shown, this embodiment provides a method for adjusting optical parameters, including the following steps: Step S1: Collect ambient light data, including ambient light intensity and ambient light color temperature; Step S2: Acquire the input video signal, parse the input video signal, and form a luminance histogram, dynamic contrast threshold, and main color gamut saturation; The target projection brightness is calculated based on the mapping relationship between the ambient light intensity and the preset human eye comfort model; Based on the ambient light color temperature and the main color gamut saturation, calculate the adaptive white balance compensation matrix; Step S3: Calculate control instructions based on the ambient light data and the input video signal. The control instructions include LCD voltage control quantity and LED current control quantity. The LCD voltage control adopts a proportional-integral control strategy, where the proportional term is the ratio of the difference between the ambient light intensity and the target projection brightness, and the integral term is the integral term of the difference between the ambient light color temperature and the image main color temperature. The LED current control adopts a differential-second-order differential control strategy. The differential term is the differential term of the entropy value of the brightness histogram, and the second-order differential term is the second-order differential term of the main color gamut saturation gradient magnitude. Step S4: Control the LCD, backlight LED and color wheel of the display device based on the control command.

[0022] The control commands include LED pulse width modulation control, LED current control, LCD voltage control, color wheel phase control, and color wheel angular velocity control.

[0023] In this embodiment, the adaptive white balance compensation matrix is ​​calculated based on the ambient light color temperature and the saturation of the image's main color gamut. It is used to compensate for the color temperature difference between the ambient light and the image content, thereby eliminating color cast. Specifically, the white balance compensation matrix is ​​integrated into the subsequent control instruction generation process. When calculating the LCD voltage control quantity, the integral term includes the difference between the ambient light color temperature and the image's main color temperature, achieving white balance compensation. Simultaneously, the processor module generates adaptive white balance compensation parameters to optimize color wheel control, including filter dwell time or LCD transmittance adjustment.

[0024] Therefore, the white balance compensation matrix is ​​used to derive the actual control quantities, including LCD voltage and color wheel phase. Through hardware actuators, including liquid crystal deflection and color wheel rotation, white balance adjustment is indirectly achieved, thus affecting the displayed image. This design avoids the delay caused by directly processing video signals and improves system response efficiency.

[0025] As a further improvement to this embodiment, the following method steps are also included: when the ambient light intensity is in the preset range of 250-400 lux and the average saturation of the input video signal is less than a preset threshold of 60%, the ambient light data, the features of the input video signal and the user operation preferences are input into a multi-mode adaptive learning engine. The multi-mode adaptive engine is a long short-term memory network. The backlight gain coefficient and color temperature offset are obtained, and the screen of the display device is adjusted based on the backlight gain coefficient and the color temperature offset.

[0026] Specifically, the multi-mode adaptive learning engine is a three-layer convolutional long short-term memory network. The input layer includes ambient light data, features of the input video signal, and user operation preferences. The convolutional layer extracts features through three sets of parallel one-dimensional convolutional kernels. The LSTM layer models temporal dependencies through a bidirectional long short-term memory network. The output layer generates backlight gain coefficients and color temperature offsets through activation functions.

[0027] The three-layer convolutional long short-term memory network comprises an input layer, a convolutional layer, an LSTM layer, and an output layer connected in sequence. The input layer receives ambient light data, features of the input video signal, and a three-dimensional tensor representing user operation preferences. Specifically, the ambient light data, features of the input video signal, and user operation preferences are represented as the ambient light intensity gradient, image color gamut volume, and historical adjustment trajectory, respectively. The convolutional layer extracts features using three sets of parallel one-dimensional convolutional kernels, with ReLU as the activation function. The LSTM layer models temporal dependencies using a 128-unit bidirectional long short-term memory network. The output layer generates the backlight gain coefficient K using Sigmoid and Tanh activation functions. b The values ​​are ∈[0.7,1.3] and the color temperature offset ΔT ∈[-500K,+500K]. The historical adjustment trajectory includes the ambient light intensity, average image saturation, color coordinates (u',v'), and the final set brightness / contrast values ​​during manual user adjustment.

[0028] Specifically, the three-layer convolutional long short-term memory network adopts a ConvLSTM network. The input layer takes into account the ambient light gradient Δlux / 100ms, the color gamut volume Δu'v' area, and the historical operation sequence. The hidden layer consists of a 3×3 convolutional layer and a 128-unit LSTM. The output layer outputs the backlight gain coefficient K. b The range is 0.7-1.3, and the color temperature offset ΔT ranges from -500K to +500K. The training period is greater than one hundred sets of data.

[0029] When the ambient light is between 250-400 lux and the average image saturation is <60%, such as when displaying natural scenery, the network architecture is represented by loading user model parameters as follows: In the input layer, the ambient light intensity gradient is the lux / 100ms value of the most recent 10 sampling points, and the sampling window is a 1-second window; the image color gamut volume is represented as V. c =(4 / 3)π·σ a ·σ b ·σ L , where σ a σ b σ L The standard deviation is the three-axis standard deviation in CIELAB space; the historical adjustment trajectory is encoded as a 20-dimensional vector, including the brightness and contrast settings of the last 5 times.

[0030] The convolutional layer consists of 3 parallel 1D convolutional kernels with sizes of 3×1 / 5×1 / 7×1 and 16 channels. The output feature map is represented as F. c =ReLU(W c *X+b c ).

[0031] The LSTM layer is used for timing modeling, specifically a 128-element bidirectional LSTM, and the state update equation is expressed as: i t =σ(W i ·[h {t-1} ,F c ]+b i [Input Gate]; f t =σ(W f ·[h {t-1} ,F c ]+b f [The Gate of Oblivion]; o t =σ(Wo·[h {t-1} ,F c ]+b o [Output Gate]; C t =f_ t ⊙C {t-1} +i t ⊙tanh(W c ·[h {t-1} ,F c ]+b c [Memory cells]; h t =o t ⊙tanh(C t [Hidden state]; The output layer is used to predict the output, and the backlight gain coefficient of the output is denoted as K. b =0.7+0.6×Sigmoid(W o1 ·F e The color temperature offset is expressed as ΔT = 1000 × Tanh (W). o2 ·F e ).

[0032] The training configuration of a three-layer convolutional long short-term memory network is as follows: the training samples include more than 100 groups for operation records; the loss function is represented by HuberLoss (δ=0.5); the optimizer is AdamW with a learning rate of 0.001 and a weight decay of 1e-4; the regularization is represented by Dropout (0.3) with a batch size of 16.

[0033] In this embodiment, the multi-mode adaptive learning engine also includes a safety constraint mechanism: a brightness upper limit protection module is set to forcibly limit the maximum projection brightness to no more than 1500 lumens when the ambient light intensity is below 20 lux; a color gamut boundary detector is activated to automatically pull back the parameters along the McAdam ellipse boundary when the color coordinates exceed the Rec.709 standard range due to user parameter adjustments; and a device aging compensation database is established to increase the backlight drive current reference value by 0.8% for every 1000 hours of accumulated running time.

[0034] Specifically, the safety constraint mechanism includes brightness protection, color gamut constraint, and aging compensation. In brightness protection, in dark environments (i.e., when the ambient light intensity is less than 20 lumens), the maximum LED current is locked at 2.0A via a hardware current-limiting circuit, corresponding to 1500 lumens. In color gamut constraint, when user adjustments cause the color coordinates to exceed the Rec.709 triangle (CIE1931), the shortest distance from the current point to the boundary of the McAdam ellipse is calculated, and the parameter is pulled back by Δu'=0.003 / step. When the cumulative running time is stored in the EEPROM, the backlight reference current increases by 0.8% every 1000 hours.

[0035] In this embodiment, the ratio term is the product of the ratio coefficient and the difference between the ambient light intensity and the target projection brightness. When the dynamic contrast exceeds a preset threshold, the ratio term increases by a preset percentage. The integral term is the product of the integral coefficient and the integral of the difference between the ambient light color temperature and the image main color temperature. When the red channel in the main color gamut saturation feature exceeds a preset threshold, the integral term is reduced by a preset ratio, activating the red filter dwell time compensation of the color wheel.

[0036] Specifically, the LCD voltage control quantity is expressed as: ; in, This represents the difference between ambient light intensity and the target projection brightness. This represents the difference between the ambient light color temperature and the image's primary color temperature. Represents the proportionality coefficient. This represents the integral coefficient, with an integration period of 20ms.

[0037] In adjusting the LCD voltage control quantity, the proportional term... It can quickly respond to sudden changes in ambient light intensity, directly responding to the instantaneous difference between ambient light intensity and target brightness, achieving rapid brightness adaptation within 50ms; the integral term can... Gradually eliminate the long-term deviation between the ambient color temperature and the image's main color temperature, and cumulatively eliminate the static deviation between the ambient color temperature and the image's main color temperature, keeping the white balance offset Δu'v' within 0.005.

[0038] The differential term is the product of the differential coefficient and the differential of the luminance histogram entropy value. When the rate of change of ambient light intensity is greater than a preset threshold, the differential term increases by a preset ratio, and the backlight pulse pre-emphasis mode is enabled. The second-order derivative term is the product of the second-order derivative coefficient and the second-order derivative of the main color gamut saturation gradient magnitude. When the dynamic contrast exceeds a preset threshold, the second-order derivative term is reduced by a preset percentage.

[0039] Specifically, the LED current control quantity is expressed as: ; in, This represents the entropy value of the brightness histogram. Indicates the magnitude of the saturation gradient in the primary color gamut. This represents the differential coefficients, with a differential interval of 10 ms. denoted by , the second-order differential coefficients, and the Laplace operator step size is 0.1.

[0040] In adjusting the LED current control quantity, the differential term... It can predict and adapt to changes in image content complexity, capture the rate of change of image brightness histogram entropy, and predict backlight requirements during HDR scene switching; second-order differential term By detecting the Laplacian operator of the saturation gradient in the HSV color space, the contrast in color boundary regions can be enhanced.

[0041] In this embodiment, the LED current control quantity is calculated using a differential-second-order differential control strategy, reflecting the backlight demand prediction based on image content, including the luminance histogram entropy value and the saturation gradient of the main color gamut. However, the LED current control quantity does not directly control the LED; the LED is driven through PWM regulation. The LED pulse width modulation control quantity is obtained by calculating the LED current control quantity, and by controlling the duty cycle of the PWM, the current intensity and pulse width of the LED are modulated.

[0042] The LED current control quantity is the target current value at the algorithm level, while the LED pulse width modulation control quantity is the PWM control signal at the hardware execution level. The two work together to ensure that the backlight can both predict content changes and suppress flicker, thereby improving image stability. Through this layered control strategy, the synergistic optimization of ambient light and image content is achieved, which not only ensures the accuracy of white balance but also improves the dynamic performance of LED backlight.

[0043] Specifically It is obtained by the difference between the real-time sampled value of ambient light intensity and the target projection brightness; The difference between the 6500K reference value representing the ambient light color temperature and the image primary color temperature (calculated by CIE 1931) is determined; The Shannon entropy value is calculated by analyzing the histogram of the Y-channel of the input video signal, and is expressed as follows: ; Let be the gradient magnitude calculated using a 3×3 convolution kernel on the HSV saturation plane, denoted as .

[0044] The initial coefficients are set as follows: =0.8, =0.05, =1.2, =0.3.

[0045] In this embodiment, the control coefficient , , , The dynamic changes and dynamic reconstruction rules for the control coefficients include: when the dynamic contrast threshold is detected to exceed 50%, Value increased by 25-35% and The value is reduced by 10-15%; if the red channel accounts for more than 40% of the main color gamut saturation feature, then... The value is reduced by 12-18% and the residence time compensation of the red filter on the color wheel is activated; when the rate of change of ambient light intensity is greater than 100 lux / s Increase the value by 20-30% and enable the backlight pulse pre-emphasis mode.

[0046] Specifically, in high-contrast scenes: when the local contrast of an image is greater than 50% (such as in text documents). It increased from 0.8 to 1.05 (+31.25%). The value was reduced from 0.3 to 0.255 (-15%), prioritizing enhancement of the luminance transient response; In red-dominant scenes: if the red channel accounts for more than 40% of the RGB histogram (such as in a sunset scene). The value decreased from 0.05 to 0.043 (-14%), and a command was sent to the color wheel controller to extend the dwell time of the red filter by 15% to compensate for the color shift. In scenarios with sudden changes in ambient light: when the rate of change in light intensity is >100 lux / s (such as switching lights on and off). Increased from 1.2 to 1.56 (+30%) and activated the backlight pulse pre-emphasis mode (current overshoot 20% for the first 3 frames).

[0047] The LED pulse width modulation control quantity is expressed as: ; in, This represents the current-to-duty cycle conversion factor, with a default value of 0.4% / mA. This represents the flicker suppression gain coefficient, with a default value of 0.15. This represents an evaluation index based on a human eye flicker sensitivity model; when the rate of change in ambient light intensity exceeds a preset threshold of 100 lux / s, the flicker suppression gain coefficient... Increasing it to 0.25 activates PWM leading-edge spike overshoot, specifically a 30% instantaneous duty cycle overshoot lasting 2ms.

[0048] LED pulse width modulation unit, based on current control quantity The PWM duty cycle adjustment is generated using a human eye flicker sensitivity model. It achieves fast brightness response and flicker suppression through pre-emphasis mode (duty cycle instantaneous overshoot of 30%) and high-frequency carrier injection technology (25kHz carrier).

[0049] In this embodiment, the control command includes a color wheel control command, which includes a color wheel phase control quantity and a color wheel angular velocity compensation control quantity. The color wheel control performs a dual-loop adjustment of phase locking and angular velocity compensation, and suppresses phase jitter within ±80 microseconds through Kalman filtering.

[0050] The color wheel phase control value is expressed as: ; The color wheel angular velocity control value is expressed as: ; in, This indicates the deviation between the actual phase of the color wheel and the frame synchronization signal, expressed in radians. and These are phase control parameters. Indicates the moment of inertia of the color wheel. This represents the damping coefficient.

[0051] In this embodiment, the control command includes a filter control command, which includes a filter dwell time control amount, expressed as: ; in, Indicates the baseline dwell time. Indicates compensation gain. Indicates the percentage of pixels in the main color gamut. This represents the total number of pixels in the image.

[0052] This embodiment employs a dual-loop control system with phase-locked loop and angular velocity compensation, combined with a Kalman filter algorithm to suppress color wheel phase jitter within ±50 microseconds, and dynamically adjusts the filter dwell time according to the proportion of the main color gamut of the image.

[0053] Example 2: This embodiment provides an optical parameter adjustment system for adjusting optical parameters using the aforementioned optical parameter adjustment method, characterized in that it includes: Ambient light sensor, used to collect ambient light intensity and color temperature data; In this embodiment, the ambient light sensor captures ambient light parameters of the projection area in real time using a four-quadrant photodetector. The spectral response range covers 380nm to 1050nm. Each quadrant is equipped with a narrowband interference filter to separate the RGB primary colors from the ambient infrared radiation, and simultaneously collects ambient light intensity (unit: lux) and color temperature (unit: K). A temperature drift compensation circuit is used to control the light intensity detection error within ±3%. 18-bit precision multispectral data is output via an I²C bus at a 120Hz sampling rate, and a built-in motion artifact detection algorithm eliminates transient interference.

[0054] Specifically, the ambient light sensor is a four-quadrant silicon photodiode array, specifically the Hamamatsu S1133. Each quadrant has a narrowband interference filter pre-positioned, set to 630±5nm for red light, 530±5nm for green light, 450±5nm for blue light, and an infrared cutoff >700nm. The ambient light sensor's sensing signal is converted to 18-bit resolution using an ADI AD7799 ADC. Temperature drift compensation is fed back to the operational amplifier reference voltage via a PT1000 thermistor. A motion artifact detection algorithm compares the differences between five consecutive frames of data; if the standard deviation is >15%, median filtering is activated.

[0055] The image analysis module is used to parse the input video signal and extract the image brightness histogram, dynamic contrast threshold, and main color gamut saturation features. In this embodiment, the image analysis module decodes each frame of video signal input from the HDMI / DP interface of the display device. Based on the histogram statistical luminance distribution probability density function, an image luminance histogram is formed; a dynamic contrast threshold is obtained based on the difference between adjacent frames; and the saturation values ​​of the main color gamut exceeding 15% in the HSV color space are identified.

[0056] The image analysis module performs the following processing steps: dividing each frame of the image into 8×8 pixel blocks and calculating the YUV space brightness variance of each block; when the variance exceeds the threshold, initiating 16×16 pixel block recombination; extracting the cluster center coordinates of the main color gamut in the a*b* plane through CIE LAB color space conversion; using the Sobel operator for edge detection to statistically analyze the proportion of high-frequency details, and generating a gamma curve segmented weight matrix accordingly.

[0057] The DSP processing flow of the image analysis module includes: Block partitioning: dividing the 1080p frame into 135×240 8×8 pixel blocks; Brightness analysis: calculating the variance of the Y component in the YUV space of each block, if it is >250 (maximum value 255), then merging them into 16×16 blocks for recombination; Color gamut extraction: after converting to CIE LAB space, performing K-means clustering (k=3) on the a*b* plane data, and taking the largest cluster center as the coordinate; Detail enhancement: using the Sobel operator (3×3 cores) to calculate the edge intensity, the proportion of high-frequency details = number of edge pixels / total number of pixels, and generating a gamma weight matrix accordingly: when the proportion of high-frequency details is greater than 30%, setting the dark gamma = 2.2 and the bright gamma = 1.8, otherwise the dark gamma = 2.0 and the bright gamma = 2.0.

[0058] The processor module is used to calculate the target projection brightness based on the mapping relationship between ambient light intensity and a preset human eye comfort model, generate adaptive white balance compensation parameters by combining ambient light color temperature and image main color gamut features, and optimize the gamma curve segment adjustment strategy according to the proportion of high-frequency details in the image. In this embodiment, the processor module includes a processing unit based on an ARM Cortex-A72 + FPGA architecture. According to the human eye comfort model of the ISO9241-307 standard, ambient light intensity is mapped to a target brightness value of 0-100%. Combining the ambient light color temperature and the image's main color gamut saturation, an adaptive white balance compensation matrix with Δu'v' ≤ 0.01 is generated. Based on the proportion of high-frequency details detected by the Sobel operator (e.g., > 30%), the gamma curve is divided into three segments for independent adjustment: dark areas (0-0.3), midtones (0.3-0.7), and highlights (0.7-1.0).

[0059] The optical actuator is used to adjust the deflection voltage of liquid crystal molecules through a three-channel synchronous driving mechanism according to the control instructions of the processor module, thereby changing the light transmittance, dynamically modulating the pulse width and current intensity of the backlight LED, and controlling the rotation phase angle and angular acceleration of the color wheel.

[0060] In this embodiment, the optical actuator is driven by a three-channel synchronous signal. The LCD control channel adjusts the deflection angle of liquid crystal molecules to change the light transmittance by outputting a 0-5V voltage. The LED control channel modulates the backlight LED current (range 0.8-1.5A) with a 100kHz PWM wave. The color wheel control channel controls the color wheel servo motor to achieve a phase angle fine adjustment of ±2° and a precise angular acceleration response of 500 rad / s².

[0061] Specifically, the optical actuator includes a liquid crystal panel temperature-voltage coupling compensation unit, which monitors the temperature difference between the panel edge and center in real time based on a thermistor array, and dynamically corrects the DC bias of the transmittance control voltage at a slope of -0.52% / ℃ ± 0.02%. The color wheel servo control unit adopts adaptive phase-locked loop technology to keep the color wheel phase strictly aligned with the image frame synchronization signal, with phase jitter controlled within 80 microseconds and angular velocity fluctuation not exceeding 0.5%.

[0062] Five NTC thermistors are embedded in the four corners and center of the LCD panel. When the temperature difference ΔT between the edge and the center is greater than 3℃, the value is calculated according to formula V. comp = V0× [1 - 0.0052×(ΔT-3)] Corrected transmittance control voltage, where V0 represents the reference voltage, thereby achieving temperature compensation.

[0063] The TI LM629 servo controller is used, and the phase of the color wheel is obtained through a 32-bit encoder and synchronized with the VSYNC signal through a phase-locked loop. The phase jitter is controlled within ±80μs, and the measures for angular velocity fluctuation <0.5% include: motor drive current ripple <2% and rotor dynamic balance level G1.0.

[0064] As a further improvement to this embodiment, a multi-mode adaptive learning engine is also included, which is used to collect ambient light parameters, image features and operation preferences when manually adjusting through the user behavior recording unit, input ambient light intensity gradient, image color gamut volume and historical adjustment trajectory, form backlight gain coefficient and color temperature offset, thereby adjusting the output screen.

[0065] Specifically, the backlight gain coefficient incorporates macroscopic backlight adjustment requirements learned based on ambient light, image content, and user historical preferences. As a feedforward or setpoint correction parameter, it is used to influence and correct subsequently calculated LED current control values. In some embodiments of this example, the backlight gain coefficient directly adjusts the LED current control value as a proportional coefficient.

[0066] Color temperature offset, as a control parameter, acts on hardware actuators such as the color wheel, thereby indirectly adjusting the overall color temperature of the image. In this embodiment, when the color temperature offset is positive, the system controls the color wheel to increase the relative dwell time of the cool color filter and adjust its phase, thereby increasing the color temperature of the projected light at the optical level. When the color temperature offset is negative, the system controls the color wheel to increase the relative dwell time of the warm color filter and adjust its phase, thereby decreasing the color temperature of the projected light at the optical level; ultimately achieving an overall color temperature offset for the image.

[0067] In some implementations of this embodiment, the color temperature offset is used as an addition or subtraction term to directly adjust the overall color temperature of the image.

[0068] Example 3: This embodiment provides a projector that achieves optical parameter adjustment using the aforementioned optical parameter adjustment method. The projector is an LCD projector, displaying the image via an LCD and using LEDs for backlighting.

[0069] Specifically, the projector provided in this embodiment integrates the optical parameter adjustment system described in Embodiment 2. The projector adds a dedicated light-transmitting window for an ambient light sensor in front of the projection lens. Its transmission spectrum curve has a transmittance of more than 90% in the 400-700nm band and a transmittance of less than 5% in the infrared band.

[0070] The projector features an 8mm diameter ambient light sensor window on the outer frame of the lens module, using a 0.5mm thick Schott BG40 glass substrate. Its transmission characteristics are as follows: transmittance is 92%, 95%, 91%, and 4% at wavelengths of 400nm, 550nm, 700nm, and 850nm, respectively. The sensor's optical axis is designed to form a 15° angle with the lens's optical axis to avoid interference with the projection light path.

[0071] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0072] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the patent application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for adjusting optical parameters, characterized in that, The process includes the following steps: collecting ambient light data, which includes ambient light intensity and ambient light color temperature; The system acquires and analyzes the input video signal to generate a luminance histogram and main color gamut saturation. Based on the mapping relationship between the ambient light intensity and a preset human eye comfort model, it calculates the target projection brightness. Based on the ambient light data and the input video signal, it calculates control commands, including LCD voltage control and LED current control. The LCD voltage control employs a proportional-integral control strategy, where the proportional term is the ratio of the difference between the ambient light intensity and the target projection brightness, and the integral term is the integral of the difference between the ambient light color temperature and the image's main color temperature. The LED current control adopts a differential-second-order differential control strategy. The differential term is the differential term of the entropy value of the brightness histogram, and the second-order differential term is the second-order differential term of the main color gamut saturation gradient magnitude. The LCD, backlight LED and color wheel of the display device are controlled based on the control command.

2. The optical parameter adjustment method according to claim 1, characterized in that, When the ambient light intensity is within a preset range and the average saturation of the input video signal is less than a preset threshold, the ambient light data, the characteristics of the input video signal, and the user's operation preferences are input into a multi-mode adaptive learning engine. The multi-mode adaptive engine is a long short-term memory network that obtains the backlight gain coefficient and color temperature offset. Based on the backlight gain coefficient and the color temperature offset, the display screen of the display device is adjusted.

3. The optical parameter adjustment method according to claim 2, characterized in that, The multi-mode adaptive engine is a three-layer convolutional long short-term memory network. The input layer includes ambient light data, features of the input video signal, and user operation preferences. The convolutional layer extracts features through three sets of parallel one-dimensional convolutional kernels. The LSTM layer models temporal dependencies through a bidirectional long short-term memory network. The output layer generates backlight gain coefficients and color temperature offsets through activation functions.

4. The optical parameter adjustment method according to claim 1, characterized in that, The scaling factor is the product of the scaling factor and the difference between the ambient light intensity and the target projection brightness. When the dynamic contrast exceeds a preset threshold, the scaling factor increases by a preset percentage. The integral term is the product of the integral coefficient and the integral of the difference between the ambient light color temperature and the image main color temperature. When the red channel in the main color gamut saturation feature exceeds a preset threshold, the integral term is reduced by a preset ratio, activating the red filter dwell time compensation of the color wheel.

5. The optical parameter adjustment method according to claim 1, characterized in that, The differential term is the product of the differential coefficient and the differential of the luminance histogram entropy value. When the rate of change of ambient light intensity is greater than a preset threshold, the differential term increases by a preset ratio, and the backlight pulse pre-emphasis mode is enabled. The second-order derivative term is the product of the second-order derivative coefficient and the second-order derivative of the main color gamut saturation gradient magnitude. When the dynamic contrast exceeds a preset threshold, the second-order derivative term is reduced by a preset percentage.

6. The optical parameter adjustment method according to claim 1, characterized in that, The LED pulse width modulation control quantity is expressed as: ； in, This represents the current-to-duty cycle conversion factor. This represents the flicker suppression gain coefficient. This represents an evaluation index based on a human eye flicker sensitivity model; when the rate of change of ambient light intensity exceeds a preset threshold, the flicker suppression gain coefficient increases, activating PWM leading-edge spike overshoot.

7. The optical parameter adjustment method according to claim 1, characterized in that, The control commands include color wheel control commands, which include color wheel phase control quantities and color wheel angular velocity compensation control quantities. The color wheel phase control value is expressed as: ； The color wheel angular velocity control value is expressed as: ； in, This indicates the deviation between the actual phase of the color wheel and the frame synchronization signal. and These are phase control parameters. Indicates the moment of inertia of the color wheel. This represents the damping coefficient.

8. The optical parameter adjustment method according to claim 1, characterized in that, The control command includes a filter control command, which includes a filter dwell time control amount, expressed as: ； in, Indicates the baseline dwell time. Indicates compensation gain. Indicates the percentage of pixels in the main color gamut. This represents the total number of pixels in the image.

9. An optical parameter adjustment system, used to adjust optical parameters by the optical parameter adjustment method according to any one of claims 1-8, characterized in that, include: Ambient light sensor, used to collect ambient light intensity and color temperature data; The image analysis module is used to parse the input video signal and extract the image brightness histogram and main color gamut saturation features; The processor module is used to calculate the target projection brightness based on the mapping relationship between ambient light intensity and a preset human eye comfort model, generate adaptive white balance compensation parameters by combining ambient light color temperature and image main color gamut features, and optimize the gamma curve segment adjustment strategy according to the proportion of high-frequency details in the image. The optical actuator is used to adjust the deflection voltage of liquid crystal molecules through a three-channel synchronous driving mechanism according to the control instructions of the processor module, thereby changing the light transmittance, dynamically modulating the pulse width and current intensity of the backlight LED, and controlling the rotation phase angle and angular acceleration of the color wheel.

10. A projector, characterized in that, Optical parameter adjustment is achieved by the optical parameter adjustment method according to any one of claims 1-8.

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