Image enhancement framework

Abstract

An image enhancement system includes an ambient light sensor, a circuit, and a processor. The ambient light sensor is operable to measure an ambient light level. The circuit is operable to generate a histogram based on an input video signal, derive the histogram, receive a gray scale lookup table, and generate an output video signal by converting a plurality of gray scales in the input video signal based on the gray scale lookup table. The processor is operable to receive the histogram from the circuit, construct the gray scale lookup table based on the histogram and the ambient light level, and communicate the gray scale lookup table to the circuit.

Description

Cross-references to related applications

[0001] This application claims the benefits of U.S. Provisional Application No. 63 / 620,255, filed January 12, 2024; U.S. Provisional Application No. 63 / 620,257, filed January 12, 2024; and U.S. Provisional Application No. 63 / 620,264, filed January 12, 2024, which are incorporated herein by reference in their entirety. Technical Field

[0002] This disclosure generally relates to systems and methods for enhancing images displayed on vehicles. Background Technology

[0003] In automotive display applications, light sensors have been used to automatically control display brightness based on ambient lighting conditions. As ambient lighting increases, display brightness increases to maintain image visibility. Automatic brightness control methods maintain a comfortable viewing brightness level and reduce display power consumption when ambient lighting decreases. While automatic brightness control methods maintain the visibility of peak white grayscale symbols, the visibility of lower grayscale values ​​may be affected. Summary of the Invention

[0004] This document provides an image enhancement system. The image enhancement system includes an ambient light sensor, circuitry, and a processor. The ambient light sensor is operable to measure ambient light levels. The circuitry is operable to: generate a histogram based on an input video signal; derive the histogram; receive a grayscale lookup table; and generate an output video signal by transforming multiple grayscale values ​​in the input video signal based on the grayscale lookup table. The processor is operable to: receive the histogram from the circuitry; construct the grayscale lookup table based on the histogram and the ambient light level; and transmit the grayscale lookup table to the circuitry.

[0005] This paper provides an image enhancement method, the method comprising: measuring ambient light level using an ambient light sensor; generating a histogram based on an input video signal using a circuit; exporting the histogram from the circuit to a processor; receiving the histogram from the circuit in the processor; constructing a grayscale lookup table using the processor based on the histogram and the ambient light level; transmitting the grayscale lookup table from the processor to the circuit; receiving the grayscale lookup table from the processor in the circuit; and generating an output video signal using the circuit by transforming multiple grayscale values ​​in the input video signal based on the grayscale lookup table.

[0006] This document provides a vehicle. The vehicle includes an ambient light sensor, a control unit, and a display panel. The ambient light sensor is operable to measure ambient light levels. The control unit is coupled to the ambient light sensor and is operable to generate an input video signal, generate a histogram based on the input video signal, construct a grayscale lookup table based on the histogram and the ambient light level, and generate an output video signal by transforming multiple grayscale values ​​in the input video signal based on the grayscale lookup table. The display panel is coupled to the control unit and is operable to generate a visible image based on the video output signal.

[0007] The above-mentioned features and advantages, as well as other features and advantages, of this doctrine will be readily understood from the following detailed description of the best mode for carrying out the doctrine in conjunction with the accompanying drawings. Attached Figure Description

[0008] Figure 1 The image illustrates a scene from the platform.

[0009] Figure 2 The figure shows a histogram of gray levels in the image.

[0010] Figure 3 The figure shows a graph of grayscale ratios.

[0011] Figure 4 The figure shows the results of the first histogram detection.

[0012] Figure 5 The figure shows the results of the second histogram detection.

[0013] Figure 6 The figure shows a graph of the first example offset gamma curve.

[0014] Figure 7 The figure shows a comparison between the constant contrast ratio method and the gamma method.

[0015] Figure 8 The figure shows the contrast ratio as a function of background brightness.

[0016] Figure 9 The figure shows an example of illuminance inside the integral hemisphere.

[0017] Figure 10 The figure shows a graph of the example endpoint slope gamma matching function.

[0018] Figure 11 The figure shows a graph of display brightness with a gamma matching function of endpoint slope.

[0019] Figure 12 The diagram shows the reflection of light from the pupil in response to blue light stimulation.

[0020] Figure 13 The figure shows the intermediate functional block diagram of the system.

[0021] Figure 14 The figure shows a functional block diagram of the image enhancement architecture.

[0022] Figure 15 The diagram illustrates the definition of the starting function.

[0023] Figure 16 The figure shows a grayscale histogram.

[0024] Figure 17 The figure shows the offset grayscale remapping.

[0025] This disclosure may have various modifications and alternatives, and some representative embodiments are illustrated by way of example in the accompanying drawings and will be described in detail herein. The novel aspects of this disclosure are not limited to the specific forms illustrated in the foregoing drawings. Rather, this disclosure is intended to cover modifications, equivalents, and combinations that fall within the scope of this disclosure as defined by the appended claims. Detailed Implementation

[0026] The embodiments of this disclosure typically provide a framework for determining a grayscale transfer function for enhancing a displayed image. The grayscale transfer function generally has three independent functions. A start function based on ambient lighting conditions is used to improve the visibility of low grayscale values. An intermediate grayscale stretching function is used to ensure the visibility of grayscale values ​​in the image. An end function is based on the whitescale image content. These three functions are stitched together using a slope-matched gamma function.

[0027] In various implementations, adaptive image enhancement (AIE) and low-level video enhancement (LVE) are provided within the framework. Adaptive image enhancement typically compensates for distortions in grayscale perceptual linearity under ambient light conditions. Adaptive image enhancement can enhance and optimize the overall perceptual brightness of image content for a given environmental condition. A roll-off function is implemented to minimize the loss of image detail. Local contrast preservation features ensure the legibility of contrast-sensitive image information. Measures are implemented for deep gray levels of the image to prevent noise enhancement due to excessive gain. It exhibits strong robustness to all types of image content, particularly all types of human-machine interface (HMI) content.

[0028] Figure 1The illustration depicts a scenario of platform 90 according to one or more exemplary embodiments. Platform 90 typically includes a dashboard 92. Dashboard 92 includes a control unit 94 and one or more display panels 100a to 100c. Dashboard 92 may be implemented as part of vehicle 93. Vehicle 93 may include mobile vehicles such as cars, trucks, motorcycles, boats, trains, and / or airplanes. In some embodiments, dashboard 92 may be part of a stationary object. The stationary object may include, but is not limited to, billboards, newsstands, and / or tents. Other types of platform 90 may be implemented to meet the design criteria of specific applications.

[0029] Control unit 94 implements one or more display driving circuits. Control unit 94 is generally operable to generate control signals to drive display panels 100a to 100c. In various embodiments, the control signals may be configured to provide instrument configurations (e.g., speed, tachometer, fuel, temperature, etc.) to at least one display panel 100a to 100c (e.g., 100a). In some embodiments, the control signals may also be configured to provide video (e.g., rearview camera video, frontview camera video, in-vehicle DVD player, etc.) to the display panels 100a to 100c. In other embodiments, the control signals may be further configured to provide alphanumeric information displayed on one or more of the display panels 100a to 100c.

[0030] In various implementations, control unit 94 typically includes at least one microcontroller. The at least one microcontroller may include one or more processors, each of which may be embodied as a separate processor, an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a dedicated electronic control unit.

[0031] At least one microcontroller can be any type of electronic processor (implemented in hardware, software executing on hardware, or a combination of both). At least one microcontroller may also include tangible, non-transitory memory (e.g., read-only memory in the form of optical, magnetic, and / or flash memory). For example, at least one microcontroller may include accompanying hardware in the form of a suitable amount of random access memory, read-only memory, flash memory, and other types of electrically erasable programmable read-only memory, as well as high-speed clocks or timers, analog-to-digital and digital-to-analog circuit systems, and input / output circuit systems and devices, and appropriate signal conditioning and buffering circuit systems. At least one microcontroller may be embedded as an FPGA or ASIC device.

[0032] The computer-readable and executable instructions embodying this method may be recorded (stored) in memory and executed as described herein. The executable instructions may be a series of instructions for running an application on at least one microcontroller (in the foreground or background). At least one microcontroller may receive commands and information in the form of one or more input signals from various controls or components in platform 90, and transmit instructions to display panels 100a to 100c via one or more control signals to control display panels 100a to 100c.

[0033] Display panels 100a to 100c are typically mounted to instrument panel 92. In various embodiments, one or more of display panels 100a to 100c may be located inside platform 90 (e.g., vehicle 93). In other embodiments, one or more of display panels 100a to 100c may be located outside platform 90. One or more display panels 100a to 100c may implement an active public / privacy viewing mode. One or more display panels 100a to 100c may also implement a privacy mode. As shown, display panel 100a may be an instrument panel display positioned for driver use. Display panel 100b may be a console display positioned for both driver and passenger use. Display panel 100c may be a passenger display positioned for both passenger and driver use.

[0034] Figure 2 The figure illustrates an example histogram 110 of grayscale in an image according to one or more exemplary embodiments. The image histogram 110 shown in the figure is primarily used to determine whether there is a small amount of higher chromaticity content in the image (e.g., on the right side of histogram 110) to allow lower chromaticity (e.g., on the left side of histogram 110) to extend. Furthermore, low video enhancement essentially shifts the image, making lower grayscale levels potentially visible.

[0035] Past human factors studies have provided insights into determining the correct function to shift lower gray levels into the visible range. Maintaining a constant contrast ratio may not be the preferred approach, as observers' contrast sensitivity typically increases with ambient lighting. In particular, a relatively low contrast ratio can be used under high lighting levels. Furthermore, forward field of view (FFOV) luminance can be considered to correct for eye adaptation mismatches when the eye is viewing a bright scene through a windshield while the ambient light level on the monitor is lower due to chromaticity conditions.

[0036] Human perceptual adaptation can be viewed as a straight line on a double logarithmic graph of display background brightness versus information display brightness. Most literature focuses on the readability of the original information. Burnette's research indicates that a minimum readability graph has also been constructed, which may be more applicable to lower brightness levels in displayed images, as lower levels (such as chromatic amplification) are typically used to display secondary information. For further details on Burnette's research, see KT Burnette's paper "The Status Quo of Human Perceptual Characteristics Data in the Design of Electronic Flight Displays," presented at the 96th AGARD Conference on Guidance and Control Displays in Paris, France, in 1972, which is incorporated herein by reference in its entirety. For further details on the utilization of the human visual system in display visibility, see Dr. Louis Silverstein and Robin Hoerner's paper "Development and Evaluation of Color Systems for Airborne Applications—Phase I: Basic Visual Perception and Display System Considerations," published in July 1985, which is incorporated herein by reference in its entirety.

[0037] frame: In various implementations, the framework is based on a combination of the Silverstein fractional power function and consideration of a constant luminance ratio between successive gray levels for ambient reflected light. An ambient light sensor is provided to measure the ambient light level, and the sensor value is proportional to the background luminance perceived by the viewer. To enable clear perception of the first gray level (GS1), the luminance level of GS1 can be increased to provide a sufficient contrast ratio between GS1 and the reflected background luminance (LBG). It may be noted that the black gray level GS0 cannot be changed and can be assigned an output GS0 value. According to the Silverstein visibility criterion, the emitted symbol luminance (ESL) can be determined by the following Equation 1: in: ESL = Emitted Symbol Luminance, measured in cd / m² 2 .

[0038] B O =Brightness offset constant.

[0039] L BG = Display background brightness, in cd / m² 2 .

[0040] c = power constant (e.g., the slope of a power function in logarithmic coordinates, usually a fraction).

[0041] For example, the minimum contrast ratio between the symbol and the background might be 5:1 at night, 3:1 at dusk, 3:1 during the day, and 2:1 in direct sunlight. Using Equation 1, the minimum brightness L perceived by the user when viewing GS1 is... Min We can assume the following equation 2: The maximum brightness that a user sees when viewing the maximum grayscale can be calculated according to the following equation 3: Where L DMax This is the maximum brightness value of the monitor.

[0042] Please note that the reflected display background brightness (LBG) has been added to both Equations 2 and 3, because this is what the user actually sees.

[0043] In order to determine L Min and L Max The concept of a constant luminance ratio is introduced by considering the grayscale luminance values ​​between these ratios. The human eye essentially perceives equal luminance ratios as equal luminance increments and can therefore distinguish all grayscale values ​​equally. Equation 4 can be used to determine the desired intermediate luminance value, as shown below: Where T is the total number of brightness levels and N is the grayscale value.

[0044] Substituting equations 2 and 3 into equation 4, we obtain equation 5, as shown below: Equation 5 can be used to determine the grayscale brightness values ​​for each of the N grayscale values ​​(N=1 to 255 and T=255) of the 8-bit per-color input.

[0045] Based on the use of more gray levels (such as a 10-bit range), the gray brightness value determined according to Equation 5 is decomposed into a new gray value GS. N Equation 6 shows the relationship between display brightness and the new grayscale value GS. N Total number of digits N New The relationship between them is as follows: The gamma symbol is represented by γ.

[0046] The next step is to understand the brightness value L determined in Equation 5. SEL Including the reflected background brightness L BG Therefore, the display brightness is determined by subtracting the background brightness. Thus, using Equations 6 and 7, the following can be established: GS N Solving equation 7 yields equation 8: After that, for L SEL We can substitute equation 5 into equation 8 to obtain equation 9, as shown below: Therefore, Equation 9 can be used to input the grayscale value of N (e.g., the number 1 to 255), and a new grayscale value GS can be determined based on the background brightness determined by the light sensor. N Grayscale determination can also be applied to red, green, and blue to maintain the correct white point. The above concepts can also be applied to extend the dynamic range of low-grayscale images.

[0047] Figure 3 Figure 120 illustrates simulated grayscale ratios according to one or more exemplary embodiments. Algo LN ratio line 122 is the ratio between consecutive grayscale values ​​of the display brightness with LVE compensation. It does not represent what the user will see. Algo LN+LBG ratio line 124 is the ratio between consecutive grayscale values ​​of the display + background brightness with LVE compensation. It represents what the user will see. γ ratio line 126 is the ratio between consecutive grayscale values ​​of the display brightness without LVE compensation. It represents what the user will see with LVE compensation. γ+LBG ratio line 128 is the ratio between consecutive grayscale values ​​of the display + background brightness without LVE compensation. It represents what the user will see without LVE compensation.

[0048] AIE grayscale extension: The method to achieve grayscale expansion or stretching is to use a constant ratio formula, as shown in Equation 9 above. For example, if Figure 2 The frame histogram shown has a detection threshold N. Max If there is a gray level, then equation 9 can be modified to set T=N. Max As shown in Equation 10 below: Please note that γ has been changed to γ D To better convey that gamma is the target display γ value. Any value greater than T NewMax The grayscale is set to T. NewMax .

[0049] Figure 4 Figure 140 illustrates the first histogram detection according to one or more exemplary embodiments. Using parameter L... BG = 100 nits and CR GS1= 1.12, if the detection threshold is determined to be grayscale 200, then N is set in Equation 10. Max The result of =200 is as follows Figure 4 As shown, LN+LBG line 142 and γ+LBG line 144 are shown.

[0050] Figure 5 Figure 150 illustrates a second histogram detection according to one or more exemplary embodiments. If the image becomes darker and the histogram detection threshold becomes N... Max =100, then use parameter L BG = 100 nits and CR GS1 = 1.12, resulting in LN+LBG line 152 and γ+LBG line 154 as follows Figure 5 As shown.

[0051] The results show that the general formula based on Equation 10 can be applied to both LVE and AIE. It also demonstrates that the simplicity of the entire system becomes apparent when the constant luminance ratio method is combined with fractional power function offset.

[0052] By taking the inner terms and assigning values ​​to variables “A” and “B”, equation 10 can be further simplified, as shown in equation 11 below: For convenience, the exponential rule is shown in the following equations 12 to 16: Using Equation 12 (the rule of exponents), Equation 11 can be rewritten as Equation 17: Applying equation (the exponential rule) 12 again, we obtain equation 18 as follows: Using equations (rules 15 and 16), equation 18 can be transformed into the following equation 19: Next, using Equation 14, Equation 19 becomes Equation 20: According to Equation 21, the exponents can be modified to a common denominator, as shown below: Adding the numerators of "A", the exponent term yields the following equation 22: Equation 22 may be the best compromise because the result is within a reasonable range. However, using equation (rule) 15, equation 22 can be further transformed to obtain the following equation 23: Finally, using equation (rule) 16, equation 23 can be transformed to obtain the following equation 24: Using the result of Equation 22, Equation 10 can be changed to Equation 25 as follows: L in the denominator of equation 25 DMax The terms can be moved outside the parentheses, as shown in equation 26 below: in: .

[0053] .

[0054] N = Input grayscale values ​​from 1 to 255.

[0055] N Max =The maximum input grayscale determined based on the input video timing data.

[0056] γ D =The gamma value displayed by the target.

[0057] L DMax =Maximum display brightness (nits).

[0058] L BG = Reflected background brightness on the monitor (nits).

[0059] B O =Fechner offset constant.

[0060] c = Fechner slope constant.

[0061] N New =The target display (including FRC) will be a new 10-bit or 11-bit value.

[0062] GS N =New mapped grayscale value.

[0063] Compared to Equation 10, Equation 26 provides a basis for a simplified implementation. Equation 27 can be achieved by using L... Max and L Min Replace them with the variables “A” and “B” from Equation 26 respectively to formulate the equation.

[0064] in: Another way to understand this system is that the maximum (L) Max ) and minimum (L) Min The brightness endpoint value is determined based on the filtered light sensor value. Then, Equation 26 calculates all new 10-bit or 11-bit values ​​between the minimum and maximum endpoints. The result using Equation 26 is that consecutive intermediate gray values ​​can have a constant visual contrast ratio, which includes reflected ambient light (L). BG The effect of ) . The new lookup table generated using Equation 27 can be used to convert 8-bit video input grayscale to 10-bit or 11-bit video grayscale output values.

[0065] The following input is used to illustrate an example of a partial lookup table in Table 1.

[0066] N Max = 255 γ D = 2.2 L DMax = 1000 nits Low BG = 100 nits B O = 11 c = 0.273 N New = 10 digits Table 1. Example of a search query

[0067] The alternative formula that can be used for Equation 27 is based on calculating the ratio once, and then multiplying the ratio N-1 by L. Min The ratio between adjacent gray levels is given by the following equation 28: Therefore, the selected grayscale brightness L sel It can be determined according to the following equation 29: However, L sel Including background brightness L BG The background brightness can be subtracted from 30 according to the following formula and equal to the target display brightness and resolution: GS N Solving this equation yields the following equation 31: R is defined in Equation 28.

[0068] Output grayscale resolution: One aspect of implementing AIE-LVE compensation is increasing the display resolution to prevent striping caused by rounding. For example, an 11-bit resolution might be appropriate to avoid seeing image artifacts.

[0069] AIE-LVE Gamma Equation: While the concept of using a constant contrast ratio perceived by the user, as described above, is the ideal way to make all chromaticities equally visible to the user, another approach is to use an offset gamma function.

[0070] Figure 6 Figure 160 illustrates a first example offset gamma curve according to one or more exemplary embodiments. As shown, the bottom of gamma curve 164 is offset from zero so that black levels become visible, and the remaining chromaticity is determined according to the gamma function. The offset between curves 162 and 164 is caused by the reflected background brightness.

[0071] The gamma curve method can be based on the following equation 32: Where: N = 0:N Max (Input video grayscale value); GS N =New grayscale value.

[0072] N Max =The maximum input gray level determined based on the gray level histogram data of the input video image; N New = Output grayscale bit levels, such as 8 bits or 10 bits; Please note that the subscripts are different for different gamma values ​​to indicate γ. D =Target display gamma (usually 2.2); and γ G =New expected gamma value.

[0073] For the new grayscale value GS N Solve equation 32, as shown in equation 33 below: Using L in Equation 26 Min Definition, Item (L) Min -L BG ) = B O (L BG ) c Equation 33 becomes Equation 34: Figure 7 Figure 170 illustrates a comparison between a constant contrast ratio method (e.g., curve 172) and a gamma method (e.g., curve 174) according to one or more exemplary embodiments.

[0074] B O Analysis of c constant: The offset B can be determined through further study of the Burnette data. O The choice of the slope constant c. Since increasing LVE raises the black level to the visibility threshold and reduces the image AIE stretch, the goal is to raise the lowest black grayscale (but not pure black grayscale 0) to the visibility level. Therefore, the analysis can begin by examining three categories on the Burnette plot: minimum threshold legibility; 50% threshold legibility; and 99% bar chart legibility (note that lower grayscale is generally not used for numerical data).

[0075] Table 2 shows some estimates. As an example, for bar chart data, Burnette points out that when the reflected background brightness is 100 fL, only 6.3 fL of the display bar brightness is visible 99% of the time.

[0076] Table 2. Data points estimated from the Burnette plot

[0077] Minimum threshold readability: Equations 35 and 36 can be formulated based on the data in Table 2 as follows: Dividing equation 36 by equation 35 yields equation 37: Equation 37 can be rewritten as Equation 38: Taking the logarithm of equation 38 yields equation 39: Since the logarithm of 10 equals 1, equation 39 simplifies to equation 40: Using the value of c determined in Equation 40, Equation 36 can be used to adjust the offset constant B according to Equation 41 below. O Solution: Therefore, Equation 1 can be written as Equation 42: 50% threshold readability: Using the methods described above and the values ​​from Table 2, the 50% threshold readability equation 43 can be determined as follows: 99% readability of bar charts: Using the method described above and the values ​​from Table 2, the 99% readability equation 44 for the bar chart can be determined as follows: The next step is to convert equations 42, 43, and 44 from imperial feet-lamberts (fL) to SI nits (cd / m²). 2 Units. The slope constant remains unchanged between imperial units and SI units; only the offset constant B... O Change. To track the system of units, label B can be used. OfL and B ONit The conversion process begins with writing the general equation in imperial units (fL) based on Equation 45 below. Note that Equations 42, 43, and 44 use imperial units.

[0078] The relationship between Foot-Lambert and Nite is shown in Equation 46 below: Therefore, in order to convert equation 45 to imperial units (fL), equation 47 can be written as follows: Therefore, equation 47 can be changed to equation 48 and simplified to equation 49 as follows: Therefore, in order to change from NIT to fL, the offset constant B is... ONit Multiply by a factor of 3.42 (C-1) .

[0079] Conversely, in order to transform fL into nits, equation 50 can be written as follows: Using the transformation factor based on Equation 46, Equation 50 can be rewritten as Equation 51 as follows: Therefore, equation 51 can be rearranged and simplified according to equation 52 to the following equation 53: Therefore, in order to transform the Foot-Lambert equation into the Nite equation, the offset constant B is shifted. OfL Multiply by a factor of 3.43 (1-C) .

[0080] Using the conversion factor according to Equation 52, Equations 42, 43 and 44 can be converted from Imperial units to SI units according to the following Equations 54, 55, 56, 57, 58 and 59.

[0081] Minimum threshold readability: 50% threshold readability: 99% readability of bar charts: Please note that the offset and slope constants are different from the values ​​used previously, where c = 0.273 and B O =11 (nits), 4.5 (fL), as shown in equations 60, 61 and 62 below: If we analyze the various equations from the perspective of contrast ratio, the result is... Figure 8 And Table 3.

[0082] Figure 8 Figure 180 illustrates the contrast ratio as a function of background brightness according to one or more exemplary embodiments. Table 3 provides a contrast ratio comparison with background brightness.

[0083] Table 3. Contrast Ratio vs. Background Brightness (fL)

[0084] Line 182 shows the smallest column. Line 184 shows the 50% column. Line 186 shows the bar chart column, and line 188 shows B. O / c column. According to Table 3, although Burnette predicts visibility at lower emission symbol luminance values, the contrast ratios differ significantly from the ISO 15008 recommendations of 5:1 for nighttime conditions, 3:1 for twilight conditions, 3:1 for daytime conditions, and 2:1 for direct sunlight conditions. To determine the various luminance categories, a model was used that converts lux illuminance levels to the background luminance perceived by the user on the display.

[0085] Figure 9 Figure 190 illustrates an example illuminance inside an integral hemisphere according to one or more exemplary embodiments. The cockpit interior can be considered as an integral hemisphere with uniform wall luminance L, such as... Figure 9 As shown. Although there are many different actual reflection components within a car cabin, many such sources that are not specular or within the haze angle range can be considered to be in the diffuse Lambertian component region. Therefore, for all light sources not in the haze / specular region, the exact angle is not crucial. The amount of light sources in the haze region typically occupies a relatively small solid angle, so it is usually not necessary to subtract these light sources to obtain the Lambertian diffuse component seen by the user. Note that once the angle of the illuminance source is greater than the haze angle, the diffuse reflectance ρ... d This is a constant (e.g., flat) and may be independent of the angle of the specular reflection reference. Therefore, all light sources with a haze angle greater than the haze angle can be combined into a single hemispherical reflectance, i.e., the total illuminance E lux multiplied by the reflectance ρ. d Divide by π.

[0086] The amount of illuminance on a small region A emanating from the center of the integrating hemisphere is given by the following equation 63: Equation 63 means that if the brightness L inside the cockpit (measured by a photometer, in cd / m²) 2 If the total illuminance (in SI units) is uniform, then the illuminance E measured at the display (in SI units) is πL. This is because the total illuminance E and the Lambert diffuse reflectance (coefficient) R (ρ) are known. d The amount of light seen by the user is given by the following equation 64: Generally, according to standard J1757-1 (16, Section 4.1), the illuminance E inside a car cabin is estimated to be approximately 5000 lux. Furthermore, when sunlight shines into the vehicle interior through the windshield, it is best to use a cosine-corrected lux meter to measure the maximum illuminance E displayed on the display. Light-colored interiors (e.g., closer to white) may exhibit a higher illuminance E than dark-colored interiors (e.g., black).

[0087] Therefore, assuming a typical high-performance anti-reflective coating display has a reflectivity of 1.5% and an indoor illuminance of 5000 lux (e.g., sunlight conditions), the background brightness can be determined according to the following equation 65: Therefore, in order to meet the ISO 15008 contrast ratio recommendation of 3:1, the display brightness can be 48 nits.

[0088] For a nighttime illuminance of approximately 10 lux, the background brightness can be determined according to the following equation 66: Therefore, in order to meet the ISO 15008 contrast ratio recommendation of 5:1, the display brightness can be 0.2 nits.

[0089] Therefore, equations 65 and 66 can be written as equations 67 and 68 as follows: Solving equations 67 and 68 yields equations 69 and 70: Due to the radical nature of the ISO 15008 results, the constants according to Equation 70 satisfy ISO 15008, but can only be used for displays with low reflectivity. This is because when the background brightness is greater than 100 nits, the brightness of lower grayscale increases dramatically and may consume the available AIE stretch range. For displays with reflectivity higher than 1.5%, a lower slope constant can be considered, as lower grayscale may still be visible according to Burnette data.

[0090] AIE endpoint enhancement: The AIE stretching function may incur a certain brightness overhead, allowing pixels exceeding a threshold limit to be differentiated to some extent, rather than limiting these pixels to the same peak display brightness value. This overhead is typically subtracted from the dynamic range of the stretched portion. In various implementations, the feasibility of specifying this overhead leads to a modification of Equation 27, where L... Max Maximum display brightness less than L DMax The maximum brightness of the display. Therefore, if the endpoint overhead % ( EPOH If %), then a new display limit brightness L can be specified according to the following equation 71. DLimit : However, sales volume can be automatically adjusted so that when N Max When the value approaches 255, the sales volume decreases according to the following equation 72: Therefore, for example, if the cost is desired for all gray levels exceeding a threshold, the stretching can be limited according to Equation 72. The method to implement this limitation is to modify Equation 27 to become Equation 73 as follows: in: ;as well as .

[0091] Please note that L DMax This can be used in Equation 73. Therefore, Equation 73 sets the maximum display brightness to L. DLimit , where N=N Max .

[0092] For video pixels exceeding a threshold, there are several ways to use additional brightness: 1. Increase the brightness above N. Max 1. Set all pixels of the threshold to maximum display brightness; 2. From L DLimit , N Max Click on L DMax 1. Perform linear interpolation at 255 points; 2. Use function matching L DLimit , N Max The slope of the point and try to hide L DLimit , N Max The dividing line of points.

[0093] The function that can be used in the third method is the gamma function. As shown in Equation 74, the gamma function has the following desirable properties: GS ΔyN = 0, where GS ΔxN = 0 GS ΔyN = GS Δy， Among them GS ΔxN = GS Δx γ EP It can be used to change the initial slope of a function. Figure 10 Figure 200 illustrates an example endpoint slope gamma matching function at endpoint 202 according to one or more exemplary embodiments. In the example, the luminance overhead is set to 90% and the background luminance level is 100 nits. Additionally, the input grayscale threshold, determined by histogram data, is set to 150. Therefore, while grayscale values ​​above 150 are compressed (e.g., line 204), higher grayscale pixels can be distinguished from each other rather than being cropped to the same maximum luminance value.

[0094] Figure 11 Figure 210 illustrates an example of display brightness utilizing the endpoint slope gamma matching function according to one or more exemplary embodiments. Figure 210 generally illustrates... Figure 10 The target display shows the conversion result of the brightness value.

[0095] The computational sequence for implementing the endpoint slope gamma matching function might be as follows: Step 1: Calculate the grayscale value of the endpoint output.

[0096] Equation 75 can be used to determine the endpoint output grayscale value GS. NEP As shown below: GS N Solving this equation yields the following equation 76: Regarding the above text Figure 11 For example, when the additional brightness 212 is defined as 90% and N Max When = 150, the result is shown in the following equation 77: Therefore, the 10-bit output endpoint is located at y=GS NEP =828.862. This value may be available in the allocation table generated according to Equation 73, since N=N Max Please note that unrounded values ​​are used to determine the slope.

[0097] Step 2: Determine the slope S at the endpoint E .

[0098] Figure 10 The slope of the endpoint of the grayscale curve shown can be determined starting from the following equation 78: Among them GS NEP-1 It is related to the input gray level N Max-1 The associated output grayscale. Therefore, Equation 73 can be modified to Equation 79 as follows for GS. NEP-1 Solution: Using the result from Equation 79, the slope can be determined from Equation 78. Note that GS NEP-1 N is in the allocation table Max The next smallest non-rounded value. For Figure 10 The example shown uses the following values, GS NEP-1 The value can be determined according to the following equation 80: in: L BG =100 nits.

[0099] L DMax =1000 nits.

[0100] c=0.273.

[0101] BO = 11 nits.

[0102] N Max = 15.

[0103] Therefore, the slope S E It can be calculated according to the following equation 81: Step 3: Calculate γ EP : Using Equation 74, the first-order slope of the gamma curve is determined according to Equation 82 as follows: Set S γ = S E We obtain the following equation 83: Equation 83 can be rearranged to provide Equation 84 as follows: Taking the logarithm of both sides of equation 84, we get equation 85: For γ EP The solution yields the following equation 86: Transforming equation 86 yields the following equation 87: Since log(1) = 0, equation 87 can be simplified to equation 88 as follows: for Figure 10 The example provided, γ EP It can be determined according to the following equation 89: Therefore, the final gamma function added to the endpoint is given by the following equation 90: For GS ΔxN = 0:(255-N Max Equation 90 becomes Equation 91: For N = 0:150, another way to write equation 91 is based on the following equation 92: The more general form of equation 92 is presented in equation 93 below: Fγ EP Functions can be added to GS NEP Value, from GS N =N Max To GS N =255. Therefore, for GS N >GN EP Equation 94 can be used.

[0104] Where N=N Max :255.

[0105] AIE-LVE Inflection Point Modifier (IPM): One way to implement an inflection point modifier is to use the concept of a sine wave, where there is a grayscale value N before the inflection point. I After the inflection point, there is a second stage. The basic concept is to multiply the grayscale value output by the original allocation table by a sine wave, and then add the result back to the grayscale value output by the original allocation table. The equations for the two stages are shown in equations 95 and 96 below: Therefore, when the input grayscale value GS N Less than or equal to the inflection point gray value N I At that time, use Equation 95 to multiply each original output grayscale value and add the result to the original output grayscale value. When the input grayscale value GS N Gray value N greater than the inflection point I At this point, Equation 96 is used to multiply each original output grayscale value, and the result is added to the original output grayscale value. Typically, one of these two amplitudes is negative. Additionally, the inflection point grayscale value can be structured as N. Max The percentage makes N in AIE Max During dynamic changes, the inflection point remains relatively in the correct position. Another feasible structure is to control the relative gain according to Equation 97, so that the inflection point amplitudes of the two stages remain relatively constant, as shown below: AIE-LVE Gamma Modifier: Gamma modifier functionality typically involves multiplying the increment of the output grayscale by a gamma function and then adding it back to the original output grayscale value of 0. Assume the naming convention is: any subscript containing an "O" represents the output grayscale value. The value following the "O" is the corresponding input grayscale value from the allocation table. Therefore, as an example, GS... O0This is the output grayscale value corresponding to the input grayscale value of 0 in the allocation table structure. Equation 98 is the form of the following gamma modifier function: Optical sensor filter coefficient: Figure 12 Figure 220 illustrates an example pupillary light reflex (e.g., curve 224) to blue light stimulation according to one or more exemplary embodiments. Curve 222 is a control curve. The light sensor filter is based on equation 99, where F... Up and F Down Use it according to the following logic: If L BGNew >L BGOld Then F = F Up；并且 If L BGNew <L BGOld Then F = F Down .

[0106] Therefore, with F=32 and a cycle time of 16.67 ms, the response time for increasing brightness can be controlled to approximately 1 second. For decreasing brightness, a value of F=2048 can be used, making the time for brightness to drop from 90% to 10% approximately 75 seconds (e.g., about 60 seconds). This method is used because the eye's rise time response is approximately 1 second, and its fall time response is approximately 60 seconds.

[0107] Figure 13 The figure illustrates an exemplary intermediate functional block diagram of a system according to one or more exemplary embodiments. In various embodiments, Figure 230 may be implemented using a field-programmable gate array (FPGA) or application-specific integrated circuit (ASIC) 232 connected to a vehicle interface processor (VIP) 234 or other processor. Each block in the figure is described below: Pixel brightness converter block 236: The pixel brightness converter block 236 converts each RGB pixel into a monochrome grayscale value based on equation 100, where the RGB coefficients are (0.19, 0.68, 0.13).

[0108] Eliminating the terms and solving for the equivalent monochrome grayscale yields equation 101.

[0109] Grayscale data accumulator block 238: According to Equation 101, each pixel is converted to a monochrome grayscale value, and for each pixel, the value 1 is added to the corresponding grayscale accumulator of each frame (by GS).Max (Accumulator composition). For 8-bit video, this will use 256 accumulators. At the end of each video frame, histogram data is sent to the vehicle interface processor 234. Additionally, a frame end trigger (FET) is sent to the vehicle interface processor 234, indicating that the accumulators are ready to be downloaded to the vehicle interface processor 234. Furthermore, the frame end trigger is used to trigger the uploading of the AIE-LVE allocation table, preparing for the next frame's video conversion. Finally, the frame end trigger is used to signal that new light sensor data is to be sampled. Light sensor sampling typically occurs once per frame period, therefore, for each frame, all functions use the same filtered data L. BG Light sensor data.

[0110] Metadata AIE-LVE bypass selector block 240: The function of bypass selector block 240 is to use metadata embedded in the video stream to identify security-related or other video symbols for which AIE-LVE enhancements have not been applied. In this case, instead of utilizing the AIE-LVE allocation table, the video of the area is sent directly to the display.

[0111] Video grayscale allocation table block 242: Grayscale allocation table block 242 uses the AIE-LVE allocation table to convert the incoming video grayscale values ​​into enhanced video grayscale values. Table 1 is an example of a video lookup table, which is uploaded by the FPGA or ASIC 232 during the video vertical blanking time to prepare for the next active video segment. The output from the grayscale allocation table can be 10-bit or 11-bit video.

[0112] 10-bit or 11-bit frame rate control block 244: Frame Rate Control Block 244 applies the Frame Rate Control (FRC) method to convert 10-bit (or 11-bit) video data into jittered 8-bit video.

[0113] Grayscale detection threshold determination block 246: Grayscale detection threshold determination block 246 determines the maximum grayscale number according to equation 102, such that a specific percentage of pixels are above the threshold percentage. Therefore, the method starts with the highest accumulator value and continuously increases the next lower accumulator value until the threshold percentage for the corresponding grayscale value is determined. This is GS Max The N value is used to filter the data through the rate-limiting filter according to block 7 into a variable N value. Max The range of dynamic video is then expanded.

[0114] Maximum grayscale filter block 248: Filter block 248 is a rate limiter, where NMax Value in each T L Time Increment Introverted GS Max The value increments or decrements by one grayscale value (8 bits). The filter rate is determined by T. L Time increment input settings.

[0115] Backlight horizontal block 250: Obtain the command backlight pulse width modulation (PWM) level and use it to determine the display brightness L according to the following equation 103. DMax L D This is the display brightness at 100% backlight drive, %. BL .

[0116] Optical sensor pre-filter block 252: The response frame end trigger (FET) sequentially measures and averages N samples from the optical sensor, and the variable L is obtained according to the following equation 104. BGNew : Please note the reflection factor R F Used to determine how much light sensor value is reflected to the user, and to perform any conversion of nits observed by the user.

[0117] Optical sensor filter block 254: According to Equation 105, the light sensor values ​​obtained in block 252 are further filtered to obtain an exponential rise time (about 1 second) that is faster than the fall time (about 60 seconds) to simulate the eye adaptation time of the human visual system and to provide peak detector functionality for the fence effect.

[0118] When the new light sensor value L BGNew Greater than the previously filtered value L BGOld When, the F value is selected as F Up And when the new light sensor value L BGNew Less than the previously filtered value L BGOld When, the F value is selected as F Down The filter's time constant was chosen to achieve a rise time of 1 second and a fall time of 60 seconds.

[0119] L Max Determine block 256: The maximum brightness observed by the user is determined according to the following equation 106, which is the endpoint display brightness (reference block 270) and the reflected background brightness L as seen by the user. BG The sum of .

[0120] L Max It is the higher endpoint of equation 27 or equation 34. Grayscale 0 calculator block 258: Grayscale 0 (GS0) needs to be handled as a special case. If the monitor does not have an active privacy feature, GS0 is set to 0 nits to achieve a black display appearance when there is no information. If the monitor has privacy features enabled, the GS0 background brightness may be increased to reduce the contrast ratio of the image. In various implementations, the Weber score level may be less than 25 for low black brightness values.

[0121] The Weber fraction is the amount of white crosstalk perceived by the driver when observing the passenger display. The "fraction" is the amount of white brightness perceived by the driver divided by the perceived black brightness, as defined in Equation 107: in: W Leakage =The amount of white leakage that the user sees; L GS0 = The amount of black brightness on the monitor; and L BG = The amount of brightness of the reflected background that the user sees at night.

[0122] Equation 107 can be rearranged to obtain Equation 108, which determines how much the black luminance value of the display can be increased to obtain a Weber score of less than 25.

[0123] In order to L Min The formula works correctly, and L BG Increase the display brightness to obtain L Min Therefore, in order to meet the Weber score criteria, L Min It can be determined according to the following equation 109: This AIE-LVE implementation assumes that the black level brightness is L. GS0 It can be increased to meet the Weber fraction requirements.

[0124] L Min Determine block 260: The minimum brightness level calculated by the allocation table is based on the larger of the following two values: the Weber fraction black brightness level calculated according to Equation 110, or the minimum brightness level calculated for display visibility according to Equation 111 below: Fechner offset B Oand slope c constant and background brightness L BG Used together to determine the minimum brightness L required for a user to barely perceive the lowest grayscale information value. Min L Min This is the lower endpoint of equation 27, as shown in Figure 39. The minimum value of the Fechner constant can be calculated according to the following equation 112: Allocation table calculator block 262: The allocation table calculation may consist of two parts. The first part is to calculate the "black" level G according to the following equation 113. S0 : The second calculation first involves selecting the available allocation table calculation method based on the "table selection" command.

[0125] 1. Constant contrast ratio allocation table 264; or 2. Gamma Allocation Table 266.

[0126] Constant contrast ratio allocation table 264: Calculate L Min With L Max The intermediate input video grayscale values ​​GS1 to GS NMax The process ensures that, taking into account the reflective environment, each consecutive gray level has the same contrast ratio, according to the reflective environment as shown in Equation 114 below: Gamma Allocation Table 266: Calculate L Min With L Max The intermediate input video grayscale values ​​GS1 to GS NMax The process allows each gray level following the offset gamma function to be determined according to the following equation 115: Allocation table modifier block 268: Block 268 provides an allocation table constructed based on Block 262 and can be modified by multiplying it by other shaping functions.

[0127] End point backlight horizontal block 270: Block 270 provides a certain amount of additional brightness that can be used in conjunction with AIE. If AIE is not used, or if no additional overhead is required, the input variable "Endpoint Overhead%" is set to zero. If "Endpoint Overhead%" is not zero, the endpoint modifier function in block 268 can be activated.

[0128] Selector S1, Metadata Control: Selector S1 block 272 has two functions. If metadata control is activated, metadata is used to bypass the AIE-LVE video allocation table, or the allocation table is used as a function of metadata. If metadata control is deactivated, the allocation table is used for all video data.

[0129] Selector S2, FRC bypass control: Selector S2 block 274 controls whether to utilize the frame rate control (FRC) function. If the display has a native 10-bit or 11-bit video input, the FRC function can be bypassed.

[0130] Selector S3, Assignment Table Upload Control: When the last video pixel of the current frame is received, selector block S3 276 is triggered as a function of the end-of-frame trigger (FET) from the FPGA (or ASIC) to upload the video allocation table. The video allocation table is uploaded during the video vertical blanking time in preparation for the next frame.

[0131] Selector S4, AIE activation control: Selector S4 block 278 controls the activation of the AIE stretch function. If AIE stretch is not activated, N will be set to... Max Set to 255, and therefore all input grayscale values ​​(e.g., 0-255) are configured to have a constant contrast ratio or in L... Min With L Max The gamma offset between them. However, if the AIE stretch function is activated, N is set according to the filtered video accumulator threshold based on blocks 246 and 248. Max .

[0132] Selector S5, proactive privacy control: Selector S5 block 280 control is used to activate black grayscale 0 brightness L. GS0 This raises the level to meet the Weber score standard. This has the effect of increasing the black level for both the driver and passengers. Due to the increased black level brightness L... GS0 The background brightness L is determined by the (ambient) light sensor. BG The function (according to Equation 108) therefore, as the reflected background brightness increases towards daylight conditions, the black level brightness L... GS0 The brightness of the black and gray tones is reduced so that they do not increase during the day.

[0133] VIP and FPGA input list and description: Table 4 is a list of the various inputs to the AIE-LVE software (or code). Variables can be stored in the Variable Control Register (VCR), which can be changed via the Controller Area Network (CAN) bus or other communication methods.

[0134] Table 4. VIP Input List Description

[0135] Architecture: Figure 14 The figure illustrates an example functional block diagram 290 of an image enhancement architecture according to one or more exemplary embodiments. This architecture typically implements an image enhancement solution (or technique) without requiring a graphics processor and associated full-frame memory. Additionally, this architecture minimizes latency and provides a cost-effective solution. As shown, FPGA (or ASIC) 292 creates histograms frame by frame (e.g., blocks 236 and 238). The histogram data is sent to VIP (Vehicle Interface Processor) 294, where VIP software 296 constructs a grayscale lookup table 298 based on the histograms and various other inputs. The table is fed back to FPGA 292 for in-line video processing. VIP 294 includes a protected area bypass data block 300, which provides data to bypass selector block 240. FPGA 292 uses the lookup table to transform grayscale levels (e.g., block 242). Additionally, FPGA 292 performs FRC functions (e.g., block 244) to simulate 10-bit to 11-bit grayscale resolution. Commercial display products typically feature a VIP (Vibration Provider Interface) to handle brightness control, touch interfaces, and temperature derating. Generally, the VIP 294 has additional bandwidth to process and handle image enhancement technologies, thus without increasing the incremental cost of providing an image enhancement solution.

[0136] AIE Starting Point Enhancement: The start-point enhancement feature operates to smooth the initial chroma from a black level, rather than letting grayscale 1 jump immediately to the LVE level. This technique creates a "start function." The start function can be stitched to... Figure 13 The main blue "GSN" function is created in block 262.

[0137] One aspect of the starting function is the use of L BG The value determines the intersection point where the starting function intersects with the AIE-LVE function. Because L... BG It depends on the reflection environment, therefore L BG The use of this automatically adjusts the intersection between these two functions. As an example, if L... BG Reducing the input gray level from 100 nits to 10 nits changes the start function, causing it to use a lower initial gray level to achieve smoothing. Note that in the example, the end of the start function decreases from an input gray level of 56 to a gray level of 32.

[0138] Figure 15 Figure 310 illustrates an example start-point function definition according to one or more exemplary embodiments. To determine the start-point function 312, the following definition is used, as shown in the figure.

[0139] N S =Starting point function and AIE-LVE GS N The grayscale value of the intersection between functions. N S It is also the final input grayscale of the starting function.

[0140] N S+1 = is a comparison of input grayscale N S The next largest integer grayscale value. This is achieved by adding 1 to N. S get.

[0141] N S-1 = is less than the input gray level N S The next integer grayscale value. This is obtained by taking N... S The result is obtained by subtracting 1.

[0142] N S0 =and Figure 13 The input grayscale value N of the transfer function used in block 262 S The associated floating-point output grayscale.

[0143] N S0+1 =and Figure 13 The input grayscale N of the transfer function used in block 262 S+1 The associated floating-point output grayscale.

[0144] Please note that the goal of the starting function is to determine the grayscale value N from the input grayscale value. S At the defined intersection point, the slope matches that of the transfer function used in block 262.

[0145] To achieve slope matching at the intersection point, one approach is to begin with a starting gamma function as shown in Equation 116 below: Where γ S The gamma slope.

[0146] The slope of the gamma function before the intersection point is defined by the following equation 117: Since the denominator is equal to 1 and N S / N S The term is also simplified to the unit one, so equation 117 is simplified to equation 118 as follows.

[0147] The aim is to make the slope of the gamma starting function equal to that of AIE-LVE GS. N The transfer function curve 314 matches. The slope of the AIE-LVE transfer function curve 314 at the intersection point can be defined according to the following equation 119: Since the denominator is equal to one, equation 119 simplifies to equation 120, as follows: Equations 118 and 120 can be combined by setting their slopes to be equal according to Equation 121: Solving for the gamma slope γ S We obtain the following equation 122: Transforming equation 122 yields the following equation 123: Taking the logarithm of both sides, we get the following equation 124: Finally, for γ S Solving for the equation yields the following equation 125: Then, the gamma value calculated according to Equation 125 is combined with Equation 116 to construct the starting function 312.

[0148] One aspect of the calculation might be N S Points are based on L BG The value developed is the same as the output value of GS1. To add some additional control, a gain factor K can be applied to the GS1 value. Therefore, Equation 126 can be used to determine the rounded integer endpoint N. S Values, as shown below: Or, N S The following equation 127 can be used to determine this: Please note that GS O1 It is derived from the background brightness value based on a power function formula. There are two forms of formula for determining the output grayscale: constant contrast ratio; and offset gamma.

[0149] The constant contrast ratio formula can be calculated based on the following equation 128: If the input grayscale is set to N=1, then equation 128 becomes equation 129: For the offset gamma formula based on Equation 130 below, if N=0, the result is the same as that of Equation 129.

[0150] Therefore, regardless of the method used, the minimum gray level is determined by Equation 129. From a brightness perspective, the display converts the minimum gray level to the following value according to Equation 131, which is exactly the brightness that conforms to Silverstein's idempotency 2-1.

[0151] Image enhancement starting point exposure: One problem with automotive display images is that lower video grayscale becomes less noticeable under reflective ambient lighting conditions. For example, a white poster board (e.g., a white shirt) reflected off a passenger seat has a brightness of 387 nits, which makes the display image appear blurry to the driver for a display with a total SCI (Surface Area Concentration) of 1.25%. Considering the human factor study by Burnette and Silverstein, 387 nits of reflected background brightness results in a display brightness of approximately 300 nits that is visible. In various cases, 300 nits corresponds to a grayscale of around 150 on a 1000-nit display. Therefore, for typical clustered displays, much of the lower grayscale content may be invisible, such as... Figure 16 The histogram is shown in the image. Due to the characteristics of the gamma function used in automotive displays, increasing the display brightness has almost no effect on reducing the visibility of video content.

[0152] Figure 16 Figure 320 illustrates an example grayscale histogram according to one or more exemplary embodiments. To address lower and intermediate grayscale visibility, display brightness standards are constantly being raised, even exceeding levels where peak white levels are visible. Therefore, image enhancement methods are becoming increasingly attractive, as they can enhance display visibility while reducing power consumption, which is becoming increasingly important for electric vehicles.

[0153] To improve the visibility of lower and mid-range video content, the lower and mid-range video levels can be dynamically adjusted to higher video levels based on ambient lighting conditions; this is known as adaptive image enhancement. Dynamic image enhancement is achieved by measuring lighting conditions and dynamically adjusting image content for better image visibility.

[0154] Adaptive Image Enhancement (AIE) provides a method to make lower grayscale content visible in a displayed image. Previously, automatic brightness control methods used light sensor information to increase or decrease the display's brightness level. These methods only addressed the visibility of upper grayscale levels in a video image. However, lower grayscale levels could remain largely invisible due to reflected brightness from the display, which often overwhelms and dilutes them. With AIE, lower grayscale levels can be made visible simply by increasing the overall brightness of the display. Furthermore, control techniques that automatically control the video path and display brightness can be integrated to provide seamless operation.

[0155] The maximum value is controlled by setting the maximum display brightness, while the minimum value is set using the grayscale function. As the reflective background brightness changes (x-axis), the minimum and maximum grayscale brightness should automatically adjust to the y-axis display brightness values. Note that the double-arrowed red dashed line represents the range of display brightness grayscale. As the reflective background increases, the range of the double-arrowed red line shifts to the right, as shown by the solid green arrow. Therefore, a light sensor can be used to estimate the reflective background brightness (L). BG ), and calculate the display brightness (ESL) amount to ensure visibility.

[0156] Before adaptive image enhancement, the highest visibility curve at the top could only be achieved by adjusting the backlight. However, by using adaptive image enhancement to adjust the video grayscale, the lowest visibility curve at the bottom can now be achieved, making lower grayscale values ​​that would normally be "diluted" by the brightness of the reflected background visible.

[0157] Figure 17 Figure 330 illustrates an example offset grayscale remapping according to one or more exemplary embodiments. To address the issue of low grayscale visibility under reflected ambient lighting conditions, the initial grayscale can be increased by 332 to, for example... Figure 17 The visibility levels are shown. In the figure, curve 334, "GS Out," represents the normal mapping on the display. Curve 336, "OS GS Out," represents the remapped grayscale using the offset gamma function.

[0158] Minimal grayscale analysis: The key feature of image enhancement is that the minimum grayscale level seen by the user remains unchanged and is independent of the maximum display brightness. Therefore, backlight brightness can be reduced to a level suitable for the relevant symbol brightness, while the minimum grayscale brightness remains constant. This concept can be explained by first understanding the overall approach of adaptive image enhancement systems.

[0159] The gray level between the start and end points is determined based on the selected function. Equation 130 above expresses the mathematical relationship for automatically recalculating lower gray levels based on display brightness.

[0160] To analyze Equation 130 above, regarding lower grayscale independence, the first step is to simplify Equation 130 by rearranging the terms described in Equation 132 below: L Max and L Min Substituting the equation into equation 132 yields equation 133, which can be used to determine the grayscale transfer function between the starting point (GS=1) and the ending point.

[0161] For ease of explanation, the values ​​used in the examples are as follows: c = 0.799; L BG = 380 nits (this is the reflected background brightness at 10K illuminance on the monitor); B O = 0.263; and γ G = γ D = 2.2.

[0162] Based on these assumptions, the amount of display brightness suitable for minimum visibility can be determined according to the following equation 134: If the minimum value N is used Max = 87, then for the lowest input gray level N=1, when the display brightness is 1000 nits and 500 nits, the first term in the numerator can be determined according to the following equations 135 and 136.

[0163] The results observed in equations 135 and 136 are smaller than the second term in the numerator of equation 133 (30.28 nits), and therefore can be ignored for N=1. Therefore, for N=1, equation 137 is implemented as follows: The actual brightness is converted to the input grayscale value N=1 using the following equation 138: Substituting equation 137 into equation 138, we obtain the following equation 139: Eliminating terms and simplifying equation 139 yields equation 140, which demonstrates that maintaining the correct low brightness level is crucial, while maintaining the display brightness L... DMax Irrelevant.

[0164] Image enhancement systems typically maintain the correct brightness level for lower chromaticity, independent of the display backlight brightness. Therefore, an automatic brightness control system can alter higher grayscale brightness levels without affecting the lowest image-enhanced grayscale brightness level. This characteristic stems from the two-point approach used in developing image enhancement techniques, where lower and higher brightness levels are determined and controlled independently, rather than using simpler image enhancement methods that only control the overall gamma function.

[0165] Those skilled in the art will recognize that terms such as “above,” “below,” “front,” “back,” “upward,” “downward,” “top,” “bottom,” etc., are used descriptively herein without implying any limitation on the scope of this disclosure. Furthermore, this teaching may describe functional and / or logical block components and / or various processing steps. Such block components may consist of various hardware components, software components executing on hardware, and / or firmware components executing on hardware.

[0166] The foregoing detailed description and accompanying drawings support and illustrate this disclosure, but the scope of this disclosure is defined only by the claims. As will be understood by those skilled in the art, various alternative designs and embodiments may exist to practice the disclosure as defined in the appended claims.

Claims

1. An image enhancement system, comprising: An ambient light sensor, operable to measure ambient light levels; The circuit is operable to: Generate a histogram based on the input video signal; Export the histogram; Receive grayscale lookup table; and An output video signal is generated by transforming multiple gray levels in the input video signal based on the gray level lookup table. as well as Processor, the processor being operable to: Receive the histogram from the circuit; The grayscale lookup table is constructed based on the histogram and the ambient light level. and The grayscale lookup table is transmitted to the circuit.

2. The image enhancement system of claim 1, wherein the construction of the grayscale lookup table involves three independent functions, the three functions providing: The start function improves the visibility of multiple low-grayscale values ​​based on ambient lighting conditions; An intermediate function ensures the visibility of image grayscale by stretching multiple intermediate grayscale levels; as well as The endpoint function distinguishes the whiteness of multiple images based on the whiteness content of the image.

3. The image enhancement system according to claim 2, wherein the construction of the grayscale lookup table comprises: Calculate the initial output grayscale; Calculate the starting slope of the association; as well as The starting function is modified based on the initial output grayscale and the associated starting slope to seamlessly stitch the starting function into the intermediate function.

4. The image enhancement system according to claim 3, wherein the construction of the grayscale lookup table comprises: The initial output grayscale is calculated using the Fechner function and the light sensor value to maintain low grayscale visibility.

5. The image enhancement system according to claim 4, wherein the construction of the grayscale lookup table comprises: The light sensor values ​​are filtered to simulate eye adaptation time.

6. The image enhancement system of claim 2, wherein the intermediate function comprises a constant contrast ratio between gray levels or an offset gamma function.

7. The image enhancement system of claim 2, wherein the construction of the grayscale lookup table comprises: The endpoint is calculated based on the percentage of grayscale values ​​in the histogram.

8. The image enhancement system of claim 7, wherein the construction of the grayscale lookup table comprises: At the endpoint, the gamma slope is matched with the gamma function.

9. The image enhancement system of claim 1, wherein the generation of the output video signal comprises: The frame rate control function is used to convert a 10-bit or 11-bit video signal into an 8-bit output video signal.

10. The image enhancement system according to claim 1, further comprising: A display panel operable to generate a visible image based on the video output signal.

11. A method for image enhancement, comprising: Use an ambient light sensor to measure the ambient light level; A circuit is used to generate a histogram based on the input video signal. The histogram is exported from the circuit to the processor; The processor receives the histogram from the circuit. Using the processor, a grayscale lookup table is constructed based on the histogram and the ambient light level; The grayscale lookup table is transferred from the processor to the circuit. The grayscale lookup table is received from the processor at the circuit. Using the circuit described above, an output video signal is generated by converting multiple gray levels in the input video signal based on the gray level lookup table. as well as A visible image is generated based on the video output signal.

12. The method of claim 11, wherein the construction of the grayscale lookup table involves three independent functions, and the three functions provide: By utilizing a start point function, the visibility of multiple low grayscale values ​​can be improved based on ambient lighting conditions; By using intermediate functions, the grayscale visibility of the image is ensured by stretching multiple intermediate grayscale levels; as well as Using an endpoint function, the whiteness of multiple images can be distinguished based on the whiteness content of the image.

13. The method of claim 12, wherein the construction of the grayscale lookup table comprises: Calculate the initial output grayscale; Calculate the starting slope of the association; as well as The starting function is modified based on the calculated initial output grayscale and the associated starting slope to seamlessly stitch the starting function into the intermediate function.

14. The method of claim 13, wherein the construction of the grayscale lookup table comprises: The initial output grayscale is calculated using a Fechner function and light sensor values ​​to maintain low grayscale visibility.

15. The method of claim 14, wherein the construction of the grayscale lookup table comprises: The light sensor values ​​are filtered to simulate eye adaptation time.

16. The method of claim 12, wherein the intermediate function comprises a constant contrast ratio between gray levels or an offset gamma function.

17. The method of claim 12, wherein the construction of the grayscale lookup table comprises: The endpoint of the endpoint function is calculated based on the gray percentage of the histogram.

18. The method of claim 17, wherein the construction of the grayscale lookup table comprises: At the endpoint, the gamma slope is matched with the gamma function.

19. The method of claim 11, wherein the generation of the output video signal comprises: The frame rate control function is used to convert a 10-bit or 11-bit video signal into an 8-bit output video signal.

20. A vehicle comprising: An ambient light sensor, operable to measure ambient light levels; Control unit, the control unit being coupled to the ambient light sensor and operable to: Generate input video signal; Generate a histogram based on the input video signal; A grayscale lookup table is constructed based on the histogram and the ambient light level; and An output video signal is generated by transforming multiple gray levels in the input video signal based on the gray level lookup table. as well as A display panel coupled to the control unit and operable to generate a visible image based on the video output signal.

Images